The most common questions about using Excel now have timely video answers. This set of quick tips offers helpful, condensed steps you can readily apply to keep on task—whether you're running calculations, setting up a new workbook, applying conditional formatting, fixing a sheet, collaborating with your team, removing sensitive information from a file, getting tables ready for a presentation, and more. Join LinkedIn Learning staff instructor Garrick Chow as he provides on-the-spot solutions for some of the most common questions in Excel. Each video is about one minute long, so you can jump in and get some helpful insights in no time. Topics include: Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Power BI Desktop—the powerful data analysis and visualization software from Microsoft—can help you get more insights from your data, whether that data is stored on your computer or in the cloud. In this course, discover how to leverage this easy-to-use tool to more efficiently model and visualize data. Learn how to connect various data sources, including Excel, databases, and web data sources like Wikipedia. Explore how to search and transform your data using the built-in Query Editor. Plus, instructor Gini von Courter shows how to build and arrange visualizations, create interactive reports, share your work, manage your published files in the Power BI service, and more. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Increased competition, globalization, and shifting technologies are just some of the contributing factors that require today's organizations to up their game to ensure the money they invest in product development is spent on the highest-valued efforts. Without a clear approach to define how programs and projects are selected, funded, and managed, organizations may end up delivering solutions that have a high probability of failure. Such failures include missing customer expectations, solving the wrong problems, or misaligning solutions with the direction the enterprise is moving. In this course, Laura Paton provides an introduction to business benefits realization, a practice designed to help organizations select the best change initiatives and ensure the proposed changes deliver and sustain business value. Laura breaks down the components of business benefits realization—introducing a five-part life cycle—and explains the steps for producing key business benefits deliverables. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Analytics is a big part of how the world does data science. But did you know that you can use applications like Excel, R, and Power BI for high-dimensional data reduction with machine learning models and algorithms? In this course, instructor Helen Wall gives you an overview of machine learning and data reduction techniques that enable you to analyze large datasets and determine trends with a variety of different classifications. Learn about machine learning models like clusters and anomaly detection algorithms. Find out more about distance, dimensionality, and granularity, as you explore dimensional and numerical data reduction techniques, analytic models, and visualization tools in Excel, R, and Power BI. Along the way, get tips on how to integrate your methods so you can scale them for sharing with a wider audience. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Excel, R, and Power BI are applications universally used in data science and across businesses and organizations around the world. If you’ve spent any time trying to figure out how to better model your data to get useful insights from it that you can act upon, you’ve most likely encountered these applications. In this course, Helen Wall shows how to use Excel, R, and Power BI for logistic regression in order to model data to predict the classification labels like detecting fraud or medical trial successes. Helen walks through several examples of logistic regression. She shows how to use Excel to tangibly calculate the regression model, then use R for more intensive calculations and visualizations. She then illustrates how to use Power BI to integrate the capabilities of Excel calculations and R in a scalable, sharable model. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Hackers target PHP web applications more often than other sites because most PHP code is written by developers with little security experience. Protecting web applications from these attacks has become an essential skill for all PHP developers. PHP: Creating Secure Websites shows you how to meet the most important security challenges when developing websites with PHP. Instructor Kevin Skoglund covers the techniques and PHP code needed to develop sites that are more secure, and to avoid common mistakes. Learn how to configure PHP properly and filter input and escape output. Then check out step-by-step defenses against the most common forms of attack, including cross-site scripting and SQL injection. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Get a thorough grounding in the concepts and skills needed for data analytics, including statistics, financial forecasting, data mining, predictive analytics, and meta-analysis. Skills: Data Analysis and Statistics Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Want to accelerate your career in data science and analytics? Consider earning the Certified Analytics Professional (CAP) credential. This premier data science certification shows potential employers that you can glean insights from data and use your findings to determine logical next steps. In the Certified Analytics Professional (CAP) Cert Prep series, Jungwoo Ryoo provides test takers with an understanding of how a core set of data science topics are relevant and necessary to obtain a CAP credential in an expedited fashion. In this installment of the series, he provides a study guide for exam domains 5–7. Plus, he shares case studies that demonstrate how the CAP knowledge domain concepts work in the real world. Topics include: Building, running, and evaluating models Calibrating models and data Validating your model performance Documenting evaluation results Developing a data model deployment approach and plan Project management approaches Tracking model quality with specific criteria Evaluating the business benefit of a model over time Managing data model life cycles Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

In the information age, companies need skilled professionals who can glean useful intelligence from troves of data. These data science roles can be challenging, rewarding, and lucrative. If you're interested in pursuing a career in this growing field, then the Certified Analytics Professional (CAP) certification may be right for you. In this course, Jungwoo Ryoo provides an expedited overview of each of the first four domains in the CAP exam, helping you get up to speed with some of the core data science concepts covered on the test. After going over the history of CAP and related certifications, he dives into domains 1–4: Business Problem Framing, Analytics Problem Framing, Data, and Methodology. Topics include: Business and analytics problem framing Collecting requirements Reformulating problem statements Metrics of success Working effectively with data Acquiring, cleaning, and sharing data Documenting and reporting findings Methodology Descriptive, predictive, and prescriptive analysis Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Not sure if you need statistics? Think again! Statistics help with making decisions, new discoveries, investments, and predictions. For subjects ranging from political races to healthcare advancements, statistics can improve your understanding of your favorite topic. In this course, Professor Eddie Davila teaches common terms, formulas, and techniques related to probability, the area of statistics where this course focuses. Eddie explains that probability is used to make decisions about future outcomes and to understand past outcomes. He covers permutations, combinations, and percentiles, and goes into how to describe and calculate them. Eddie introduces multiple event probabilities and discusses when to add and subtract probabilities. He describes probability trees, Bayes’ Theorem, binomials, and so much more. You can learn to understand your data, prove theories, and save valuable resources—all by understanding the numbers. Topics include: Define and explore the basics of probability. Discuss and examine permutations and combinations. Explain how to calculate percentiles. Define the concept of conditional probability. Introduce and use probability trees. Define and utilize Bayes’ theorem. Discuss and explore discrete random variables. Introduce binomials and discuss their relation to normal curves. Examine bell-shaped curves and what they represent. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Statistics is not just the realm of data scientists. All types of jobs use statistics. Statistics are important for making decisions, new discoveries, investments, and predictions. Whether the subject is political races, sports rankings, shopping trends, or healthcare advancements, statistics is an instrument for understanding your favorite topic at a deeper level. In this course, Professor Eddie Davila offers beginner-level lessons, so you too can master the terms, formulas, and techniques needed to perform the most common types of statistics. Eddie covers several examples of data and charts. He explains how to find the middle of your data set, as well as the mean and median. He introduces range, then goes into standard deviation and what to do with outliers. These techniques help you understand your data, prove theories, and save time, money, and other valuable resources—all by understanding the numbers. Topics include: Introduce the concepts of mean, median, and mode. Explain how to calculate range. Explore the z-score concept. Define standard deviation. Introduce the empirical rule. Explore how standard deviation and normal distributions are related. Recognize the possible role of outliers. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Since the inception of data analytics, the way in which analysts view and interpret data has evolved tremendously. New technologies, tools, and approaches have advanced what's possible with data analytics, and network analysis is no exception. In this course, longtime data analyst and data visualization expert Heather Johnson shares the fundamentals of using graph analytics, or network analysis, when analyzing data. Heather begins by reviewing the components of a network analysis and detailing the advantages of using a graph analytics approach. She then walks through key applications of using graph analytics when reviewing data. To wrap up the course, Heather discusses career opportunities within the realm of graph analytics. Upon completion, you’ll be equipped with the knowledge of what graph analytics is and how it can be leveraged within your analytics career. Topics include: Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

In the world of data analytics, you're consistently presented with the same decision when it comes to how you'll communicate your data and insights. For each project, you need to decide whether to use a dashboard or tell a data story. In this course, business intelligence architect Sara Anstey provides you with the necessary information you need to make this decision with confidence. First, Sara covers the fundamentals of making decisions with data and shares how the role of a data analyst makes this possible for organizations. She then dives into the topics of data science dashboards and data storytelling, highlighting the pros and cons of each and providing the details you need to determine which approach is right for you. Sara closes by recapping key concepts, leaving you prepared to pick between each of these options with ease and intentionality. Topics include: Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

It’s one thing to work with data. It’s another to provide quality data sets and accurate visualizations for decisions to be made. If you are considering a course emphasis or a career in data analytics, this course can help you get off to a good start. Robin Hunt, CEO and co-founder of ThinkData Solutions, shares practical skills to help you get the most from your data and jumpstart your career in data. Robin discusses business rules, filtering out the noise in the data we all deal with, and how to deliver what decision-makers want. She covers how to create data sets with queries, joins, and appends, then goes into building aggregate data with total queries. Robin goes over pivots, how to use pivots to build basic dashboards and visualizations, and how to use Power Query for data transformations. She concludes with best practices for meetings and taking your work to the next level for your organization. Topics include: Explore concepts relating to data analytics. Explain the use of wildcard characters in building queries. Review types of data visualizations. Describe how slicers are used. Define terminology used in creating visualizations. Differentiate between duplicate and reference data sets. Identify licensing and permissions considerations. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

How do reusable services contribute to the management of large volumes of data? How do can they reduce the data volume? Or garantee its quality? And control storage and handling cost?

A proper predictive analytics and data-mining project can involve many people and many weeks. There are also many potential errors to avoid. A "big picture" perspective is necessary to keep the project on track. This course provides that perspective through the lens of a veteran practitioner who has completed dozens of real-world projects. Keith McCormick is an independent data miner and author who specializes in predictive models and segmentation analysis, including classification trees, cluster analysis, and association rules. Here he shares his knowledge with you. Walk through each step of a typical project, from defining the problem and gathering the data and resources, to putting the solution into practice. Keith also provides an overview of CRISP-DM (the de facto data-mining methodology) and the nine laws of data mining, which will keep you focused on strategy and business value. Apply for this course

Big data is transforming the world of business. Yet many people don't understand what big data and business intelligence are, or how to apply the techniques to their day-to-day jobs. This course addresses that knowledge gap, giving businesspeople practical methods to create quick and relevant business forecasts using big data.Join Professor Michael McDonald and discover how to use predictive analytics to forecast key performance indicators of interest, such as quarterly sales, projected cash flow, or even optimized product pricing. All you need is Microsoft Excel. Michael uses the built-in formulas, functions, and calculations to perform regression analysis, calculate confidence intervals, and stress test your results. You'll walk away from the course able to immediately begin creating forecasts for your own business needs. Apply for this course

Analytics is such a broad topic that it´s hard to know where to get started. In this course designed for students, explore how to use data analytics to make informed decisions, and build core analytics skills that can prepare you to enter into the business or data science landscape. Learn about the basics of analytics, how data is typically captured, and how it impacts the day-to-day of a business. This course also provides an introduction to common tools used in analytics, as well as stories designed to help students get an overview of careers that require strong analytical skills. Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in. This course is in French only. If this is not a problem for you, by all means go ahead and apply. Apply for this course

Are you interested in pursuing a career in data analytics? In this course, instructor Robin Hunt brings you into the mind of an analyst. She defines and explains foundational concepts, such as how to think about data, how to work with others in different roles to get the data you need, and the tools you need to work with data, such as Excel and Microsoft Access. She introduces you to SQL queries, PowerBI, and more. Robin goes into syntax and explains how to interpret the data you see, find the data you need, and clean the data for effective data work. She explains data governance and how to ask the right questions of different departments to gather the data you need. Robin shows how to work with data, including how to import data, work with flat files such as CSVs, and create datasets for others. Robin goes into what cleaning and modeling mean, as well as how to use Power Query in Excel. She has also added challenge/solution sets in each chapter to help you evaluate your skills. Apply for this course

We are wired for story. We crave it. Storytelling has played an integral role in our ability to make progress. It should come as no surprise, then, that presenting data and information in story form maximizes the effectiveness of our communication. We can create deeper emotional responses in our audience when we present data in story form.Join data visualization expert Bill Shander as he guides you through the process of turning "facts and figures" into "story" to engage and fulfill our human expectation for information. This course is intended for anyone who works with data and has to communicate it to others, whether a researcher, a data analyst, a consultant, a marketer, or a journalist. Bill shows you how to think about, and craft, stories from data by examining many compelling stories in detail. Apply for this course

Many anthropologists believe our early ancestors built societies around campfire stories about justice, leadership, and government. Your data science teams will also have complex ideas about their data and results. That's why it takes a well-structured story to communicate these insights to the rest of your organization. It's not simply a matter of creating the perfect Excel sheet or a beautiful graph. You need to tell a story that captures your audience's imagination and encourages them to take some action. In this course, instructor Doug Rose explains how to weave together a great data science story and draw your audience into the story to communicate complex ideas and motivate everyone to make real changes. Apply for this course

Data visualization is ultimately the make-or-break moment for any data science operation or business analytics project. Develop a solid foundation for how to think about the visual interpretation and communication of data and data insights. Apply for this course

Computer-enhanced artificial intelligence (AI) has been around since the 1950s, but recent hardware innovations have reinvigorated the field. New sensors help machines have more accurate sight, hear sounds, and understand location. Powerful processors can help computers make complex decisions, sort through possibilities, plan outcomes, and learn from mistakes. The possibilities are thrilling; the implications are vast.This course will introduce you to some of the key concepts behind artificial intelligence, including the differences between "strong" and "weak" AI. You'll see how AI has created questions around what it means to be intelligent and how much trust we should put in machines. Instructor Doug Rose explains the different approaches to AI, including machine learning and deep learning, and the practical uses for new AI-enhanced technologies. Plus, learn how to integrate AI with other technology, such as big data, and avoid some common pitfalls associated with programming AI. Apply for this course

Do you know the difference between AI and machine learning? Do you know how they affect you, your career path, and the world around us? After taking the courses in this learning path, you'll have a mastery of the concepts and future directions of technologies like artificial intelligence and machine learning. You'll be able to make more informed decisions and contributions in your work environment. Gain a clear and detailed understanding of how AI and machine learning work. Learn how leading companies are using AI and machine learning to change the way they do business. Learn how the next generation of thinking about AI is addressing issues of accountability, security, and explainability. Apply for this course

Learn the most popular data-science-specific language: R! This learning path provides a strong foundation of skills and knowledge on which to build your coding resume. Learn how R works, from the foundational concepts on up. Practice using R with two of the most common tools in data science: Excel and Tableau. Explore the applied use of R in social network analysis. Apply for this course

The R language is one of the top two languages you need to learn if you want build the strongest career path possible in data science. (The other is Python.) After mastering the basics of R, take your skills in data science into highly valued areas of specialty with this learning path. Learn R in the context of the R tidyverse. Create data visualizations and presentations. Develop business analytics skills at an advanced level in Excel. Apply for this course

Data integrity is the new focal point of the data science revolution. Now that everybody is onboard with the role of data in people's lives and business, it's not an unfair question to ask, "Can you prove that your data is accurate?" In this course, you can learn how to identify and address many of the data integrity issues facing modern data scientists, using R and the tidyverse. Discover how to handle missing values and duplicated data. Find out how to convert data between different units and tackle poorly formatted text. Plus, learn how to detect outliers, address structural issues, and identify red flags that indicate potential data quality issues.Where possible, instructor Mike Chapple shows how to correct the issues using R, but the same principles can be applied to any statistical programming language. Learning objectives Missing data Duplicate rows and values Converting data Formatting data Working with tidy data Tidying data sets Dealing with suspicious data Apply for this course

If you want to participate in the data revolution, you need the right tools and skills. R is a free, open-source language for data science that is among the most popular platforms for professional analysts. Learn the basics of R and get started finding insights from your own data, in this course with professor and data scientist Barton Poulson. The lessons explain how to get started with R, including installing R, RStudio, and code packages that extend R’s power. You also see first-hand how to use R and RStudio for beginner-level data modeling, visualization, and statistical analysis. By the end of the course, you’ll have a thorough introduction to the power and flexibility of R, and understand how to leverage this tool to explore and analyze a wide variety of data. Apply for this course

Analyzing big data is great, but not if you can't share your results. In this course, Martin Hadley shows how to create interactive presentations of large data sets with R, RStudio, and Shiny, an R-based tool for producing interactive, web-ready data visualizations. Learn why these tools are important to data scientists, how to configure and install them, and how to use them to make your findings more clear and engaging.Discover the different types of presentations you can make right out of the box with R Markdown templates (built right into RStudio) and how to customize the templates with CSS. Find out how to register for RPubs to deploy RStudio presentations for sharing, and then go beyond the basics with Shiny—adding interactivity and creating embeddable dashboards without the need for HTML or JavaScript.This is an exciting course for analysts who want to increase the relevance and visibility of their work. Make sure to watch the knowledge checks at the end of each chapter to test your new skills. Apply for this course

Discover how to create informative and visually appealing data visualizations using ggplot2, the leading visualization package for R. In this course, Mike Chapple shows how to work with ggplot2 to create basic visualizations, how to beautify those visualizations by applying different aesthetics, and how to visualize data with maps. Throughout the course, Mike also covers key concepts such as the grammar of graphics and how to apply different geometries to visualize data. To wrap up, he shares a case study that lends a practical context to the concepts covered in the course. Apply for this course

Tidy data is a data format that provides a standardized way of organizing data values within a dataset. By leveraging tidy data principles, statisticians, analysts, and data scientists can spend less time cleaning data and more time tackling the more compelling aspects of data analysis. In this course, learn about the principles of tidy data, and discover how to create and manipulate data tibbles—transforming them from source data into tidy formats. Instructor Mike Chapple uses the R programming language and the tidyverse packages to teach the concept of data wrangling—the data cleaning and data transformation tasks that consume a substantial portion of analysts' time. He wraps up with three hands-on case studies that help to reinforce the data wrangling principles and tactics covered in this course. Apply for this course

R is known as one of the most robust statistical computing solutions out there. Tableau—a leading business intelligence platform—provides excellent data visualization and exploration capabilities. When combined, Tableau and R offer one of the most powerful and complete data analytics solutions in the industry today, providing businesses with unparalleled abilities to see and understand their data. In this course, learn how to integrate these two platforms, as well as how to determine when each one is a better choice. Instructor Ben Sullins explains how to connect Tableau to R, and covers geocoding, running linear regression models, clustering, and more. Apply for this course

R is an incredibly powerful and widely used programming language for statistical analysis and data science. The "tidyverse" collects some of the most versatile R packages: ggplot2, dplyr, tidyr, readr, purrr, and tibble. The packages work in harmony to clean, process, model, and visualize data.This course introduces the core concepts of the tidyverse as compared to the traditional base R. It focuses on the novice user and those unfamiliar with the pipe (%>%) operator. After covering these R basics, instructor Martin Hadley progresses to importing and filtering data from Excel, CSV, and SPSS files, and summarizing and tabulating data in the tidyverse. Then learn how to identify if data is too wide or long and convert it if necessary, and conduct nonstandard evaluation. By the end of the course, you should be able to integrate the tidyverse into your R workflow and leverage a variety of new tools for importing, filtering, visualizing, and modeling research and statistical data. Apply for this course

If you want to participate in the data revolution, you need the right tools and skills. R is a free, open-source language for data science that is among the most popular platforms for professional analysts. Learn the basics of R and get started finding insights from your own data, in this course with professor and data scientist Barton Poulson. The lessons explain how to get started with R, including installing R, RStudio, and code packages that extend R’s power. You also see first-hand how to use R and RStudio for beginner-level data modeling, visualization, and statistical analysis. By the end of the course, you’ll have a thorough introduction to the power and flexibility of R, and understand how to leverage this tool to explore and analyze a wide variety of data. Apply for this course

Trying to locate meaning and direction in big data is difficult. R can help you find your way. R is a statistical programming language to analyze and visualize the relationships between large amounts of data. This training series provides a thorough introduction to R, with detailed instruction for installing and navigating R and RStudio and hands-on examples, from exploratory graphics to neural networks. In part one, instructor Barton Poulson shows how to get R and popular R packages up and running and start importing, cleaning, and converting data for analysis. He also shows how to create visualizations such as bar charts, histograms, and scatterplots and transform categorical, qualitative, and outlier data to best meet your research questions and the requirements of your algorithms. Apply for this course

Using the R language almost exclusively, htmlwidgets allow you to create the same interactive maps, charts, and graphs you see on popular data journalism sites and in BI dashboards. You can connect R to popular JavaScript libraries—such as Plotly and Leaflet—with htmlwidget packages. The interactive visualizations you create can be used in R Markdown reports and presentations, and even integrated into rich, responsive Shiny applications. This course introduces you to the fundamental skills needed to add htmlwidgets to your R workflow.Start by learning to manage packages and structure data for visualizations with the tidyverse and the pipe operator. Then there is an important question: Which library should you choose? The course introduces five popular options: Leaflet, Plotly, Highcharter, visNetwork, and DataTables (DT). Instructor Martin Hadley shows how to use these libraries to create scattergeo, choropleth, and geolines maps; stacked bar charts, scatter charts, bubble charts, and heat maps; treemaps and time series charts; interactive networks and graphs; and responsive, interactive data tables. Plus, learn how to customize your visualizations with legends and tooltips, and extract click information for Shiny apps. Apply for this course

Data scientists who use Excel realize that R is emerging as the new standard for statistical wrangling (especially for larger data sets). This course serves as the perfect bridge for the many Excel-reliant data analysts and business users who need to update their data science skills by learning R. Much of the course focuses on how crucial statistical tasks and operations are done in R—often with the DescTools package—as contrasted with Excel functions and Data Analysis add-in, and then scales up from there, showing the more powerful features of R. Conrad Carlberg helps you effectively toggle between both programs, moving data back and forth so you can get the best of both worlds. Learn about calculating descriptive statistics, running bivariate analyses, and more. Apply for this course

Data fills all available space, and now that storage is cheap, the amount of data has exploded. However, all that information is useless without analysis and context. The R programming language is designed to make it easier to analyze and visualize massive amounts of data. For example, R provides the ability to multiply one block of variables by another—an assumption that provides inherent advantages over other languages. This course shows why R is ideal for high volumes of data, introduces more efficient ways to use the language, and explains how to avoid the problems and capitalize on the opportunities of big data. Learn how to determine if you have enough memory and processing power, produce visualizations of big data, optimize your R code, and use advanced techniques such as parallel processing to speed up your computations. Plus, discover how to integrate R with big-data solutions such as SQL databases and Apache Spark. Learning objectives Accessing memory and processing power Visualizing high-volume data Profiling and optimizing R code Compiling R functions Parallel processing with R Using R with other big data solutions Apply for this course

R is powerful, but not intuitive. There is a strong and diverse R ecosystem, and data scientists are expected to mix and match from the different versions and packages. Before you can even begin programming, you have to choose, install, and set up R to work for you.In this course, Mark Niemann-Ross provides a direct and efficient introduction to the many flavors of the R programming language, including base R, tidyverse R, R Open from Microsoft, and Bioconductor R. He also provides a peek at programming with R interactively and via the command line, and introduces some helpful packages for working with SQL, 3D graphics, data, and clusters in R. At the end of this short course, you will have installed a version of R along with a few core libraries and an optimized IDE. Apply for this course

Social Network Analysis Using R teaches analysts how to visualize and analyze data from a social network like Twitter or Facebook with the text-based statistical language, R. If you're involved in analytics in any capacity, this course will be a huge help, teaching you how the R sna and igraph modules works and how to format data for analysis, create graphs, analyze network graphs, and visualize networks. Join instructor Curt Frye and learn how to examine the relationships and trends among networks in new and exciting ways, and discover information about how individuals in an organization interact. Apply for this course

Make your data beautiful; turn it into an infographic. Infographics make complicated information easily understandable and visually compelling. In this course, Nigel French memorializes the soldiers and events of World War I, but you can use these lessons to build almost any kind of infographic. Learn how to use Illustrator, InDesign, Photoshop, and Excel together to analyze and chart the data, plot locations on a map, and build a timeline that simply details a complex sequence of events. Along the way, Nigel explains how to choose fonts and color, create a background image, and finally convert your print graphic into a format suitable for websites. Apply for this course

Got a big idea? You need to get it across quickly and efficiently, or modern audiences will move on to the next story clamoring for their attention. Data visualization allows you to make the complex simple, the abstract tangible, and the invisible (data) visible with great illustrations. In this course, Bill Shander shows how to understand your data and your audience, craft the story you need to tell, and determine the best visual model and details to use for that story. Apply for this course

Media and marketing efforts often rely on data visualizations to quickly prove a point. But poorly designed visualizations can be misleading. Whether it's choosing the wrong charts or graphs, misinterpreting the data, or showing it without context, inaccurate designs can become a source of global scrutiny.To succeed in design and marketing today, one must know how to interpret and properly visualize data. This course, developed and led by Killer Infographics CEO, Amy Balliett, walks you through the ins and outs of creating accurate and compelling data visualizations. Amy focuses on best practices, not tools, although she does provide an overview of Illustrator graphing features. Using these tips, you'll learn how to stand out from the crowd and create charts and graphs that combine precision with visual appeal. Apply for this course

As a data analyst, you probably already know how to build visualizations and use tools like Excel and Tableau. This course challenges you to go beyond the data, beyond the software, and start thinking more clearly and strategically about the foundations of great communication design. Bill Shander, founder of Beehive Media, focuses on the key challenges that analysts face trying to communicate complex information, and how visual communication can help. He breaks down ten key components of great data visualizations—built in any program—and shows innovative ways of rethinking the slides, charts, diagrams, and dashboards you work with every day. Apply for this course

Data Visualization Tips and Tricks is a series of standalone lessons on how to do data viz the right way, every time. Presented by award-winning data visualization expert (and Tableau-designated "Zen Master") Matt Francis, this software-agnostic course is designed for experienced data scientists and analytics specialists and serves as a must-have bank of knowledge and best practices. Learn how to choose the right visualization for your data, and answer the 5 key questions you should ask yourself at the beginning of every project. Topics include understanding the relationships between data sets, making comparisons, charting relationships, visualizing data distributions, creating maps, and—most valuably—knowing when to use which types of graphs and charts. Matt also teaches you how to understand what others are doing with their own visualizations, ask informed questions, and look with a critical eye at the work of others. Apply for this course

Big data is transforming the world of business. Yet many people don't understand what big data and business intelligence are, or how to apply the techniques to their day-to-day jobs. This course addresses that knowledge gap by showing how to use large volumes of economic data to gain key business insights and analyze market conditions.Professor Michael McDonald demonstrates how to harness the wealth of information available on the Internet to forecast statistics such as industry growth, GDP, and unemployment rates, as well as factors that directly affect your business, like property prices and future interest rate hikes. All you need is Microsoft Excel. Michael uses the built-in formulas, functions, and calculations to perform regression analysis, calculate confidence intervals, and stress test your results. He also covers time series exponential smoothing, fixed effects regression, and difference estimators. You'll walk away from the course able to immediately begin creating forecasts for your own business needs. Apply for this course

Predictive analytics is one of the richest disciplines within the realm of data science. As the tools and techniques for using data to predict future outcomes have evolved, business and data analysis professionals can use this learning path to stay up to date with the latest advancements. Apply for this course

Building world-class predictive analytics solutions requires recognizing that the challenges of scale and sample size fluctuate greatly at different stages of a project. How do you know how much data to use? What is too little, what is too much? How does your infrastructure need to scale with the volume and demands of the project? This course walks step by step through the strategic and tactical aspects of determining how much data is needed to build an effective predictive modeling solution based on machine learning and what volumes of data are so large that they will create challenges. Instructor Keith McCormick reviews each stage—data selection, data preparation, modeling, scoring, and deployment—with scalability in mind, providing IT professionals, data scientists, and leadership with new insights, perspectives, and collaboration tools.Note: This course is software agnostic. The emphasis is on strategy and planning. Examples, calculations, and software results shown are for training purposes only. Apply for this course

Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to conduct exploratory data analytics with GCP. First, review the concepts of segmentation and profiling. Then get hands on, as you learn to perform both text and visual analysis of data using tools provided by GCP: Cloud Datalab, BigQuery, Cloud Dataflow, and Data Studio. Finally, look at an end-to-end use case that applies what you've learned in the course. Learning objectives Setting up Cloud DataLlb for exploratory data analytics Segmentation and profiling Reading and writing data from BigQuery Managing cloud storage buckets Creating visualizations of BigQuery data with the GCP Charting API Managing Datalab instances Apply for this course

Predictive analytics use historic data to look forward, enabling organizations to make better decisions. However, making accurate predictions from big data can be an overwhelming task. Enter Google Cloud Platform (GCP), a suite of cloud-computing services that bring scalability, elasticity, and automated machine learning to predictive analytics. This course—one of a series by data scientist Kumaran Ponnambalam—shows how to apply the power of GCP to generate predictions for your business. Start off by exploring the different tools and features for predictive analytics in GCP, including Cloud Dataproc, Cloud ML Engine, and the machine learning APIs such as Cloud Translation, Cloud Vision, and Cloud Video Intelligence. Then explore learn how to build, train, and deploy models to create predictions. Plus, learn best practices for cost control, testing, and performance monitoring of predictive models. Apply for this course

Discover how to make smarter product pricing decisions that maximize your organization's profits. In this course, instructor Michael McDonald goes over using scenario analysis, price optimization, and variance analysis to model the data analytics behind pricing . Michael explains how to determine bundle pricing in a scenario, estimate price elasticity, compute price optimization profits with one variable or many variables, balance price and sales volume considerations, and more. If you'd like to pursue a career in corporate finance—particularly as a pricing analyst in an insurance, retail, manufacturing, or technology firm—then this course can help equip you with the skills you need to help your company succeed in today's economy.. Apply for this course

Business analytics encompasses a set of tools, technologies, processes, and best practices that are required to derive knowledge from data. It's an iterative and methodical exploration of data to derive insights from it—and, in turn, make smarter, more strategic decisions that are grounded in facts. In this course, learn about the stages in business analytics that are used to predict and build the future—predictive analytics, prescriptive analytics, and experimental analytics. This course dives into each stage, discussing the tools and techniques used for each, as well as best practices leveraged in the field. In addition, the course lends a real-world context to these concepts by using a use case to demonstrate how to execute analytics in each stage. Apply for this course

Business analytics allows us to learn from the past and make better predictions for the future. There are three types of analytics used for learning from the past. Descriptive analytics summarizes historical data; exploratory analytics uncovers hidden patterns; and explanatory analytics reveals the reasons for business results. Each type encompasses a different set of tools, technologies, processes, and best practices to derive insights from data. This course by Kumaran Ponnambalam explains why they matter and how and when to use them.He starts by setting the context for business analytics and its various stages. You then explore the stages that focus on the past: descriptive, exploratory, and explanatory. With each stage, you learn about the processes, techniques, and best practices used in the field. Finally, you walk through a use case (the results of an email marketing campaign) that demonstrates how analysis is performed at each stage. Learning objectives Business analytics and its stages Descriptive analytics Exploratory analytics Explanatory analytics Best practices and use cases Apply for this course

Many modern organizations have a wealth of data that they can draw from to inform their decisions. But all of this information can't truly benefit a business unless the professionals working with that data can efficiently extract meaningful insights from it. Amazon Web Services (AWS) offers data scientists an array of tools and services that they can leverage to analyze data. In this course, learn about best practices, patterns, and tools for designing and implementing data analytics using AWS. Explore key analytics concepts, common methods of approaching analytics challenges, and how to work with services such as Athena, RDS, and QuickSight. Plus, discover how to visualize text-based data in a more visually intuitive way, use partner solutions for analytics from the AWS Marketplace, and more. Apply for this course

Software containers are the future of app deployment—and an instrumental component of any DevOps strategy. They package everything a program needs to run, allowing developers to move applications from one environment to another relatively hassle free. In this course, cloud-computing luminary David Linthicum dives into the exciting world of software containers. David goes over the basics of containers, including an overview of the fundamental steps involved in building container-based software, followed by some examples of real-world applications that leverage containers. The course concludes with container standards and best practices, and the tools, processes, and skills a DevOps professional needs to work with them. Topics include: Containers vs. virtual machines When vs. when not to use containers Building new apps with containers Moving existing apps to containers Example container applications Standards, tools, processes, and skills Apply for this course //

By automating configuration management, you can make your organization's systems more reliable, processes more repeatable, and server provisioning more efficient. In this course, learn the basics of infrastructure as code, including how to keep your configuration in a source repository and have it built and deployed like an application. Discover how to approach converting your systems over to becoming fully automated—from server configuration to application installation to runtime orchestration. Well-known DevOps practitioners Ernest Mueller and James Wickett dive into key concepts, and use a wide variety of tools to illustrate those concepts, including Chef, CloudFormation, Docker, Kubernetes, Lambda, and Rundeck. After you wrap up this course, you'll have the knowledge you need to start implementing an infrastructure as code strategy. Topics include: Testing your infrastructure Going from infrastructure code to artifacts Unit testing your infrastructure code Creating systems from your artifacts Instantiating your infrastructure from a defined model Provisioning with CloudFormation Immutable deployment with Docker Container orchestration with Kubernetes Apply for this course //

DevOps is not a framework or a workflow. It's a culture that is overtaking the business world. DevOps ensures collaboration and communication between software engineers (Dev) and IT operations (Ops). With DevOps, changes make it to production faster. Resources are easier to share. And large-scale systems are easier to manage and maintain. In this course, well-known DevOps practitioners Ernest Mueller and James Wickett provide an overview of the DevOps movement, focusing on the core value of CAMS (culture, automation, measurement, and sharing). They cover the various methodologies and tools an organization can adopt to transition into DevOps, looking at both agile and lean project management principles and how old-school principles like ITIL, ITSM, and SDLC fit within DevOps. The course concludes with a discussion of the three main tenants of DevOps—infrastructure automation, continuous delivery, and reliability engineering—as well as some additional resources and a brief look into what the future holds as organizations transition from the cloud to serverless architectures. Topics include: What is DevOps? Understanding DevOps core values and principles Choosing DevOps tools Creating a positive DevOps culture Understanding agile and lean Building a continuous delivery pipeline Building reliable systems Looking into the future of DevOps Apply for this course //

Many organizations deliver products with dozens or even hundreds of teams. For these organizations, spinning up a few agile teams is just the start. Eventually, they'll want to scale up their agile approach to work on enterprise-level products—a shift that presents a whole new set of challenges. Enterprise agile requires a different organizational mindset along with new roles and practices. There are many different enterprise agile frameworks that will help you with this transformation, but switching to these frameworks isn't your biggest challenge. Enterprise agile is a radical change from how most organizations think about their work. If you don't prepare your teams for this change, then it's unlikely that any enterprise framework will succeed.That's why this course is the first in a four-part series on enterprise agile. In this course, Doug Rose helps you lay the groundwork you'll need to make this radical organizational change. First, learn how to identify your organization's culture. There are many different types of organizational cultures, and each one presents its own set of challenges. Then, see different approaches to making a widespread organizational change. Finally, learn about the common challenges that almost all organizations face when starting enterprise agile.Topics include: Establishing the groundwork Understanding the change Reviewing organizational culture Identifying your organizational culture Trying the Kotter approach Being fearless Evangelizing change Changing myths Focusing on culture Dealing with common challenges Apply for this course //

By applying lean and agile principles, engineering teams can deliver better systems and better business outcomes—both of which are crucial to the success of DevOps. In this course, instructors Ernest Mueller and Karthik Gaekwad discuss the theories, techniques, and benefits of agile and lean. Learn how they can be applied to operations teams to create a more effective flow from development into operations and accelerate your path of "concept to cash." In addition to key concepts, you can hear in-the-trenches examples of implementing lean and agile in real-world software organizations. Apply for this course //

Customer needs change every day. We need our products to keep up. Take an agile approach to requirements analysis: Learn the mindset and techniques necessary to discover requirements for an agile project and succeed in the business analyst (BA) role. Angela Wick reviews the 12 agile principles from a BA's perspective, introduces backlog management techniques, and discusses techniques such as product decomposition, user stories and story maps, which help BAs deliver products that truly delight customers. Plus, find out what concepts such as "minimum viable product" and "value stream" mean to people in the BA role. Apply for this course //

Leadership—the art of influencing and developing others to achieve their highest potential—is often identified as the most critical role in an organization. But what is effective leadership and how do you cultivate it? In this course, leadership consultant and global workforce expert Dr. Shirley Davis covers the basics of leading yourself and others. Along the way, she identifies the critical competencies and best practices for effectively leading today and in the future. Learn how to lead across differences and cultivate a more inclusive workplace; establish trust; build relationships up, down, and across the organization; lead change through agility and resilience; have difficult conversations; and more. Apply for this course //

Learn how to communicate more effectively. Your communication skills affect your career prospects, the value you bring to your company, and the likelihood of your promotion. This course helps you communicate better in a variety of professional situations, including meetings, email messages, pitches, and presentations. Instructors Tatiana Kolovou and Brenda Bailey-Hughes introduce the four building blocks of communication—people, message, context, and listening—and show how they apply in different circumstances. Through the use of vignettes and applied tools, the course shows how to build this core competency and communicate in a way that effectively and professionally conveys your message. Apply for this course //

Communication is an integral part of strong teamwork. In this course, Kelley School of Business professor Dr. Daisy Lovelace walks managers through how to cultivate the communication practices of high-performing teams. She highlights the foundations of successful teams, and explains how to craft a team charter to establish ground rules for how you work together as a cohesive group. She also discusses essential elements of team communication—such as creating a shared vision and holding teammates accountable—and shows how to best communicate with your team in different settings. Apply for this course //

Communicating effectively isn't an innate talent that some people have and others don't—it's something that anyone can learn and practice. In this course, learn strategies that can help you hone and master your interpersonal communication skills. Join personal branding and career expert Dorie Clark as she shares techniques for getting your message across effectively in the workplace, and explains how to tackle potential communication challenges with your colleagues and supervisor. She also discusses how to grapple with tricky situations, taking you through how to handle interruptions, respond to critical feedback, and communicate across cultures. Apply for this course //

To define great requirements, it's not enough to simply ask customers and stakeholders what they want. By leveraging requirements elicitation and analysis techniques, business analysts can come up with more innovative solutions. In this course, explore these techniques, and learn why they're important, and how to blend them together and tailor them to your project. Angela Wick provides an overview of the process, and discusses how elicitation and analysis work together. She also covers different ways of gathering requirements—such as brainstorming, observation, and workshops—before moving on to analysis techniques such as context diagrams, user stories, and decision tables. At the conclusion of the course, she explains how to select the right approach for a particular product or project type. Apply for this course

Getting the requirements right in software development is half the battle. In this course, instructor Neelam Dwivedi delves into the techniques and tools needed to win that battle. Neelam reviews the different types of requirements and how to divide your requirement development process into phases. She covers how to elicit, specify, analyze, and validate product requirements, sharing challenges along the way that help you grasp how these phases work in real-world projects. Plus, she shares techniques for estimating effort for requirements, as well as how to minimize or mitigate project risk by working iteratively on high-risk requirements first. Learning objectives What are requirements? Requirement development phases Elicitation techniques Functional vs. nonfunctional requirements Defining user stories and use cases Mapping data input and output requirements Validating requirements Apply for this course

Slow loading times can drive users away from even the most elegant website or application. But how can you pinpoint where your product's performance issues lie? In this course, join Dave Westerveld as he details the fundamentals of performance testing, including when and how to use the different types of tests and tools at your disposal. Discover how to determine what to measure and how to monitor the results of your tests. Explore the different types of performance testing—including load, stress, and scalability tests—and the contexts in which it's appropriate to use each of them. Plus, learn about a broad set of tools and how to pick the right one for the work you need to do. Learning objectives Why do performance testing? Determining what to measure Finding and identifying bottlenecks Using load, stress, endurance, and spike testing Logging and parsing data Load testing and network interception tools Apply for this course

Modeling with the Unified Modeling Language (UML)—a visual design language for object-oriented programming—is a critical skill for all team members in a software development project. These models are a cost-effective way for collaborators to analyze, communicate, and document their product's characteristics. In this course, learn how to use UML diagrams to create important artifacts at each stage of the software development life cycle. Instructor Neelam Dwivedi shares best practices and tools as she goes over 13 different types of UML models, explaining what you need to know to develop static and dynamic models of software systems. Learning objectives How UML differs from other modeling techniques Types of UML models UML modeling tools Use case, activity, and class diagrams Capturing real-time state of your system in action Using component diagrams Interaction overview diagrams Modeling time-constrained interactions Apply for this course

All good software starts with a great design. Object-oriented design helps developers plan applications before they write a single line of code, and break down ideas into reusable and maintainable components. This course focuses on the foundational concepts, teaching them in a fun, interactive way to help you quickly develop your skills. Tag team Olivia and Barron Stone introduce you to the concepts and terms—objects, classes, abstraction, inheritance, and more—that you need to get started. They then show how to take the requirements for an app, identify use cases, and map out classes using Universal Modeling Language (UML). The final design can then be translated into code using one of the many popular object-oriented programming languages, such as Java, C#, Ruby, or Python. Learning objectives Object-oriented basics: objects, classes, and more Encapsulation Inheritance Defining requirements Identifying use cases, actors, and scenarios Domain modeling Identifying class responsibilities and relationships Creating class diagrams Using abstract classes Working with inheritance Developing software with object-oriented design principles Apply for this course

Most people have heard of RESTful APIs, but the underlying concept—representational state transfer (REST)—still causes confusion. REST is all about modeling resources that change. RESTful APIs use REST architecture along with HTTP requests to transfer data and changes in application state between clients and servers. This course breaks down the principles of RESTful design and show how to build secure RESTful APIs on top of ASP.NET Core. Nate Barbettini answers questions such as: What is RESTful design? How do you perform RESTful routing? How can you build reusable classes to represent resources? What role does caching play? And how do you secure RESTful APIs? He also covers topics such as data modeling, hypermedia relationships, and authentication and authorization. By the end of the course, you should know the basics—how to properly request and return data in ASP.NET Core—and the best practices for building secure and scalable APIs to serve web clients, mobile clients, and beyond. Topics include: What is RESTful design? Building a new API with ASP.NET Core Using HTTP methods Returning JSON Creating RESTful routing with templates Versioning Securing RESTful APIs with HTTPS Representing resources Representing links Representing collections Sorting and searching collections Building forms Adding caching to an ASP.NET Core API Configuring user authentication and authorization Apply for this course

Learn the basics of REST APIs. In this course, discover what REST APIs are, why they matter, and how putting them to use can help you build faster, more efficient applications. Review how HTTP and REST APIs relate, explore the six constraints of REST, and learn about HTTP status messages. Learn how to get started with consuming REST APIs to incorporate them into data-driven applications. Topics include: What is a REST API? Who or what interacts with REST APIs? Anatomy of a REST request HTTP status messages Request/response pairs GET, POST, and DELETE Apply for this course

Why use GraphQL over REST APIs? GraphQL is better at querying multiple databases, offers an easy-to-learn syntax, and allows you to retrieve only the data you need. Learn when you should migrate from REST to GraphQL, and how to convert your REST API add, update, and delete operations into GraphQL mutations. Instructor Emmanuel Henri also explains how to build simple, useful queries; use arguments, fragments, and aliases in queries; and perform operations using GraphQL. Learning Objectives: Setting up GraphQL Creating the initial schema and type Setting up simple queries Leveraging arguments and aliases Reading, updating, adding, and deleting items with GraphQL Posting data with mutations Apply for this course

Knowing how to work efficiently and securely with APIs is crucial in software development. Learn RESTful APIs from the ground up as a new or experienced developer, filling in any foundational knowledge gaps around HTTP requests and how to validate an API's behavior. If you are consuming, designing, or maintaining an API, this learning path is for you. Follow this path with tech-specific API courses of your choosing to apply your knowledge in practical project-based courses. Skills: Back-End Web Development, Application Programming Interfaces, Front-end Development Apply for this course

The ability to successfully build a RESTful web service is an essential skill in today's Internet-dominated industry. In this course, learn how to develop a RESTful client and server application using the Java Enterprise Edition implementation of the REST architectural style, JAX-RS API 2.0. This powerful and fully-featured API enshrines industry best practices as it integrates seamlessly with other essential APIs such as Bean Validation and JSON Processing. Join Alex Theedom as he guides you through a wide range of topics, including how to define resource endpoints, how to add dynamism to your application with hypermedia, how to maintain data integrity with Bean Validation, and how to process messages with the JSON Processing API. Once you have completed this course, you'll be ready to develop your own client and server RESTful APIs. Topics include: Discover the extent of JAX-RS's features Use the annotation methodology Use the inheritance methodology Define a REST contract and API root Create the REST resource entity Create the REST resource methods Understand consumers and producers Work with different media types Define and work with path parameters Build a REST response and handle exceptions Implement Bean Validation and manage failures Create a RESTful client that consumes the web service Use JSON-P API with the REST client Implement hypermedia (HATEOAS) Apply for this course

Most API testing doesn't actually test the API. This course shows how to validate your API from the consumer's point of view, testing to confirm that problems experienced by your end users are being solved. Join Keith Casey as he focuses on how to approach API testing by implementing a behavior-driven development model. Keith uses Gherkin to set up a Behat environment so you can see how to write and run your first test. Then, he shows how to build API test requests, including how to introduce variables, authenticate requests, and validate responses. He also covers refactoring tests, establishing system states, using extensions for batch operations, and more. Apply for this course

Web services have been at the core of modern application architectures for many years. Regardless of what language or platform a developer is using, grasping how web services work and how to implement them are critical skills. In this course, instructor Kesha Williams steps through how to work with several popular technologies to build web services. Kesha begins by laying the groundwork for the course, explaining what web services are and the benefits they provide. She then offers a comparison of several popular web service technologies—REST, SOAP, and GraphQL—describing each technology's messaging formats in detail, along with examples of coding in several languages using a variety of server- and client-based implementations. Plus, get coding excerpts in Java, Python, and Swift. Apply for this course

Version control is an essential skill for developers to master, and Git is by far the most popular version control system on the web. In this fast-paced course, author Ray Villalobos shows you how to install Git and use the fundamental commands you need to work with Git projects: moving files, managing logs, and working with branches. Plus, you'll learn how to work with the popular GitHub website to explore existing projects, clone them to your local hard drive, and use them as templates for your new projects. Get started now. Want to explore Git and GitHub in more depth? Watch Git Essential Training for more comprehensive coverage of these tools. Apply for this course

Development teams transitioning to distributed source control with Git often experience friction when initially adopting the tool. Often, the root cause is related to issues surrounding culture and practices as opposed to a technical learning curve. In this course, Kevin Bowersox covers collaboration strategies for teams using Git, discussing tools and techniques that can help you and your team circumvent the challenges that hinder the delivery of high-quality software. Kevin shares best practices and tips that can help you avoid common pitfalls that often cause teams to veer off track. Learn branching strategies, how to build a continuous integration pipeline, and more. Topics include: Identifying team conventions and best practices with Git Avoiding common pitfalls Teaming with remote platforms Implementing Git worklow and branching strategies Building a continuous integration pipeline Building a DevOps foundation Apply for this course

Having a solid understanding of how to correctly build APIs is important for any developer planning on creating websites. In this course, learn how to plan and model your own APIs, and explore the six REST design constraints that help guide your architecture. Keith Casey starts with a simple overview, including advice on identifying the users or "participants" of your system, and the activities they might perform with it. He discusses how to validate your design before you build it, and explores the HTTP concepts and REST constraints needed to build your API. To wrap up, Keith goes over some of the most common API design patterns you may encounter. Topics include: Approaches to adding an API Modeling tips Identifying activities and breaking them into steps Mapping activities to verbs and actions Creating and grouping API methods Validating your API HTTP headers and response codes Common design challenges Versioning best practices Hypermedia and documentation approaches Apply for this course

Le diagramme de classes UML (Unified Modeling Language) peut convenir parfaitement à la modélisation d’une base de données. Avec votre formateur Christian Soutou, vous découvrirez tous les mécanismes à adopter afin de construire vos modèles relationnels d’une manière optimale et de générer vos scripts SQL. Vous pourrez appliquer ces principes à n’importe quel système de gestion de base de données (SGBD) du marché (Oracle, SQL Server, DB2, MySQL, PostgreSQL, etc.). Cette formation suit les niveaux du processus de conception d’une base de données. Elle présente aussi méthodiquement les concepts et les solutions de chaque étape. Que vous soyez développeur, analyste ou chef de projets, découvrez UML sous un autre jour ! Apply for this course

When it comes to negotiation, shifting your mindset from "a battle to be won" to "a problem-solving conversation" can improve your results dramatically. In this course, leadership coach, negotiation expert, and author Lisa Gates demonstrates the core skills of interest-based negotiation to get win-win outcomes every time. Learn a step-by-step strategy for negotiating everyday workplace issues, from asking for a raise or promotion to pitching ideas and resolving conflict. Lisa covers techniques such as diagnostic questions, anchoring, framing, and labeling, which help you navigate impasse and generate satisfaction on both sides of the bargaining table. Along the way, discover how to prepare for a negotiation, cultivate your influence, get into a zone of agreement even when you have to say "no," and negotiate remotely over phone or email. Lisa also shares her best negotiation tips and tricks and provides worksheets to practice your skills. Apply for this course

Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. It has now been updated and expanded to two parts—for even more hands-on experience with Python. In this course, instructor Lillian Pierson takes you step by step through a practical data science project: building machine learning models that can generate predictions and recommendations and automate routine tasks. Along the way, she shows how to perform linear and logistic regression, use K-means and hierarchal clustering, identify relationships between variables, and use other machine learning tools such as neural networks and Bayesian models. You should walk away from this training with hands-on coding experience that you can quickly apply to your own data science projects. Apply for this course

Data science provides organizations with striking—and highly valuable—insights into human behavior. While data mining can seem a bit daunting, you don't need to be a highly-skilled programmer to process your own data. In this hands-on course, learn how to use the Python scientific stack to complete common data science tasks. Miki Tebeka covers the tools and concepts you need to effectively process data with the Python scientific stack, including Pandas for data crunching, matplotlib for data visualization, NumPy for numeric computation, and more. Apply for this course

Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. It has now been updated and expanded to two parts—for even more hands-on experience with Python. In this course, instructor Lillian Pierson takes you step by step through a practical data science project: a web scraper that downloads and analyzes data from the web. Along the way, she introduces techniques to clean, reformat, transform, and describe raw data; generate visualizations; remove outliers; perform simple data analysis; and generate interactive graphs using the Plotly library. You should walk away from this training with basic coding experience that you can take to your organization and quickly apply to your own custom data science projects. Apply for this course

Data science is transforming the way that government and industry leaders look at both specific problems and the world at large. Curious about how data analysis actually works in practice? In this course, instructor Michele Vallisneri shows you how, explaining what it takes to get started with data science using Python. Michele demonstrates how to set up your analysis environment and provides a refresher on the basics of working with data structures in Python. Then, he jumps into the big stuff: the power of arrays, indexing, and tables in NumPy and pandas—two popular third-party packages designed specifically for data analysis. He also walks through two sample big-data projects: using NumPy to identify and visualize weather patterns and using pandas to analyze the popularity of baby names over the last century. Challenges issued along the way help you practice what you've learned. Note: This version of the course was updated to reflect recent changes in Python 3, NumPy, and pandas. Apply for this course

Due to its power and simplicity, Python has become the scripting language of choice for many large organizations, including Google, Yahoo, and IBM. A thorough understanding of Python 3, the latest version, will help you write more efficient and effective scripts. In this course, Bill Weinman demonstrates how to use Python 3 to create well-designed scripts and maintain existing projects. This course covers the basics of the language syntax and usage, as well as advanced features such as objects, generators, and exceptions. Learn how types and values are related to objects; how to use control statements, loops, and functions; and how to work with generators and decorators. Bill also introduces the Python module system and shows examples of Python scripting at work in a real-world application. Apply for this course

Modern work in data science requires skilled professionals versed in analysis workflows and using powerful tools. Python can play an integral role in nearly every aspect of working with data—from ingest, to querying, to extracting and visualizing. This course highlights twelve tips and tricks you can put into practice to improve your skills in Python. These techniques are readily applied and in common data management tasks and include the following: how to ingest data using CSV, JSON, and TXT files; how to explore data using libraries like Pandas; how to organize and join data using DataFrames; how to create charts and graphic representations of data using ggplot in Python; and more. Apply for this course

A sizable portion of a data scientist's day is often spent fetching and cleaning the data they need to train their algorithms. In this course, learn how to use Python tools and techniques to get the relevant, high-quality data you need. Instructor Miki Tebeka covers reading files, including how to work with CSV, XML, and JSON files. He also discusses calling APIs, web scraping (and why it should be a last resort), and validating and cleaning data. Plus, discover how to establish and monitor key performance indicators (KPIs) that help you monitor your data pipeline. Apply for this course

Data visualization is incredibly important for data scientists, as it helps them communicate their insights to nontechnical peers. But you don’t need to be a design pro. Python is a popular, easy-to-use programming language that offers a number of libraries specifically built for data visualization. In this course from the experts at Madecraft, you can learn how to build accurate, engaging, and easy-to-generate charts and graphs using Python. Explore the pandas and Matplotlib libraries, and then discover how to load and clean data sets and create simple and advanced plots, including heatmaps, histograms, and subplots. Instructor Michael Galarnyk provides all the instruction you need to create professional data visualizations through programming. Apply for this course

Python—the popular and highly readable object-oriented language—is both powerful and relatively easy to learn. Whether you're new to programming or an experienced developer, this course can help you get started with Python. Joe Marini provides an overview of the installation process, basic Python syntax, and an example of how to construct and run a simple Python program. Learn to work with dates and times, read and write files, and retrieve and parse HTML, JSON, and XML data from the web. Apply for this course

Quickly learn the general programming principles and methods for Python, and then begin applying that knowledge to using Python in data science-related development. Learn the basics of Python as an object-oriented programming language. Apply Python coding skills to analytics uses. Explore the Python scientific stack of tools. Apply for this course

With this course, gain insight into key statistical concepts and build practical analytics skills using Python and powerful third-party libraries. Instructor Michele Vallisneri covers several major skills: cleaning, visualizing, and describing data, statistical inference, and statistical modeling. All concepts are introduced by analyzing intriguing real-world datasets and discussed from a machine-learning perspective—which assumes that powerful computation can replace complex mathematics. Apply for this course

Implement namespaces, extend interfaces, create your first Trait, dive into object-oriented programming, and discover versatile scripting methods with this course. Web developer Justin Yost takes you into the advanced parts of the PHP server-side language, including abstract classes, iterators, generators, and password hashing. He provides an overview of each topic, takes you through how to code each item for the first time, and then shows you how to expand further. Learn how to establish consistency, solve problems, and prevent your applications from crashing by applying the techniques Justin shares in this course. Take your object-oriented programming beyond basic attributes and methods into using constructors, deconstructors, and singletons. Build nested exceptions, use type hints, and explore additional ways you can craft more flexible software using PHP. Topics include: Namespaces Standard interfaces Traits Constructors, deconstructors, and singletons Cloning objects Abstract classes Iterators Generators Password hashing and verification Type hints, strict type hints, and return types Advanced closures Nested exceptions and SPL exceptions Apply for this course

PHP 7 is the first major release of PHP in more than 11 years. This course by expert instructor Kevin Skoglund provides an overview of the new features, improvements, and changes in PHP 7. Learn about new tools to help write smarter code, and the key changes you need to watch for to ensure your existing PHP code works correctly after an upgrade. Topics include: Scalar type and return type declarations New operators in PHP 7 Anonymous classes Arrays as constants Catchable exceptions and errors Integer division with intdiv() Deprecations and deletions Apply for this course

For large tech organizations, the path to agile adoption is hardly ever a smooth one. If you're aiming to implement agile at scale, then this course can help by letting you know which pitfalls you may encounter and providing techniques for successfully managing a transformation. Instructor Jez Humble dives into the key principles that are at the heart of high-performance program management. He also provides a case study that showcases an iterative and adaptive approach to running large programs and discusses the importance of continuous improvement. Apply for this course

Artificial intelligence (AI) offers businesses the potential for a dramatic increase in functionality and profitability, but it can also spark an array of complex ethical, legal, and social challenges. In this nontechnical, conceptually oriented course, Barton Poulson digs into the hazards of AI, offering potential solutions to key concerns. Barton explores the ethical issues posed by AI, including competing concepts of fairness and moral reasoning. He also goes over social concerns and safety challenges for AI, such as potential life-and-death scenarios in autonomous driving. Barton concludes with recommendations tailored to developers, executives, PR professionals, regulators, and consumers to help them reap the potential of AI in a manner that's worthy of trust and profitable to all. Apply for this course

Machine learning is one of the liveliest areas in artificial intelligence. Machine learning algorithms allow computers to learn new things without being programmed. They use statistics as a way to better understand the massive amounts of data that we create every day. These newer algorithms help machines classify images, sounds, and videos. They can answer our questions, discover new drugs, and even write songs. In this course, we review the definition and types of machine learning: supervised, unsupervised, and reinforcement. Then you can see how to use popular algorithms such as decision trees, clustering, and regression analysis to see patterns in your massive data sets. Finally you can learn about some of the pitfalls when starting out with machine learning. Apply for this course

An artificial neural network uses the human brain as inspiration for creating a complex machine learning system. There are now neural networks that can classify millions of sounds, videos, and images. These machines can answer our questions, understand our behaviors, and even drive our cars. The network looks for subtle patterns in our data and then fine-tunes itself to improve over time. They can become experts in predicting our behavior, learning our languages, and finding new discoveries. In this course, instructor Doug Rose provides an overview of artificial neural networks, explaining what they are and how you can use them for your machine learning challenges. Discover ways that you can use this technology to do fascinating new things for your projects or your business. Apply for this course

Cognitive technologies such as artificial intelligence and robotics are changing how businesses operate and the nature of work as we know it. This course, from Deloitte University Press, is designed to explain the benefits and value of cognitive technologies to business leaders, decision makers, and others who want to understand their impact on business. David Schatsky focuses on the "what" and "why," leaving you to craft a "how" that meets your organization's needs. He covers machine learning, artificial intelligence fields such as natural language processing and computer vision, and robotics. In later chapters, David examines the business case for the technologies, looking at practical applications for products and processes. Finally he reviews the impact on workers and the design of work, and takes a look forward into the future of cognitive tech. Short quizzes and assessments help you practice your knowledge. By the end of the course, you should be able to engage in productive discussions with colleagues, customers, and suppliers and help shape the cognitive technology strategy at your organization. Apply for this course

Deepak Agarwal is the VP of artificial intelligence (AI) at LinkedIn, a company on the frontline of data science. LinkedIn is heavily invested in AI and machine learning, transformative technologies that can improve all aspects of member experience. This investment is demonstrated in the LinkedIn AI Academy, which trains engineers and other employees on the power, potential, and best practices for developing and using AI tools. In this Q&A style course, Deepak discusses how LinkedIn leverages AI and machine learning, the ways the technology influences our lives, and what's to come, including advice for those wondering "Will AI take our jobs?" and "What skills can I learn in order to start a career in AI?" Apply for this course

Artificial intelligence (AI) is no longer confined to the realm of science fiction. It's on track to disrupt the world of work in a very real way, and major changes—from the rise of productization to the demand for predictability—are driving its adoption. In this course, learn about the impact that AI will have on project management, how to prepare for the changes that lie ahead, and how to harness the power of AI to work smarter. Instructor Oliver Yarbrough goes over the factors that are contributing to the growing importance of AI. He also details how to prepare for the disruption that it will cause; hone the skills that AI cannot replace; and leverage AI to more effectively initiate, plan, execute, monitor and control, close, and integrate your projects. Apply for this course

Now that AI and machine learning are widespread, people are starting to ask, "Is the technology actually making the best decisions? Can AI be trusted? How and where do humans fit in?" Explainable artificial intelligence (XAI) is a solution that increases transparency about how AI systems make decisions and take actions. This course provides a solid introduction of how XAI works and the value it provides to data science-related businesses and initiatives from legal and commercial perspectives. Instructor Aki Ohashi, director of business development for PARC, a Xerox company, bridges the gap between AI's potential and pitfalls, presenting executives, entrepreneurs, managers, and team leaders with exactly what they need to know to stay on top of how AI affects their fields. He uses real-world examples and cases studies to show what XAI is, how it works, how it's being used right now, and where it may have the most impact in the future. Apply for this course

There's a critical link between an organization's goals and its performance metrics. A beautiful mission statement is nothing without specific, actionable measures that provide incentives to succeed. These actionable numeric measures are called key performance indicators (KPIs) and can be organized into a structure called the balanced scorecard. The scorecard helps you quantify business performance over time: weeks, months, quarters, or even years. In this course, accounting professors Jim and Kay Stice explain what KPIs your business should consider in a balanced scorecard, from financial goals to employee and customer satisfaction. They describe how to craft a clear mission statement that complements your KPIs, and how to tie performance to incentives. Plus, get a look at KPIs in action, as Jim and Kay break down a case study examining a trucking company's balanced scorecard. Learning Objectives: The importance of KPIs and measuring performance Financial goals and measure Customer needs and satisfaction Employee growth Employee growth Creating an effective mission statement Linking measurements and rewards Examining a KPI case study Apply for this course

The Green Belts or Black Belts that lead Lean Six Sigma projects are well-trained and ready to guide your project to the finish line. But what do you, as a team member on a Lean Six Sigma project team, need to know to be effective? In this course, Dr. Richard Chua provides coverage of fundamental Lean Six Sigma concepts that can help you add value to your project. Here, he focuses on key tools and techniques in the Define and Measure phases of the DMAIC—Define, Measure, Analyze, Improve, and Control—approach. Discover how Lean Six Sigma integrates lean into DMAIC. Learn about the project charter, process mapping, using Pareto charts to identify problem areas, and more. For information about the final three phases of DMAIC, make sure to check out the next installment of the Lean Six Sigma Teams series. Topics include:● How Lean Six Sigma integrates lean into DMAIC ● Understanding the purpose and steps of the Define phase ● Using process and value stream maps ● Using SIPOC to define the process and its key stakeholders ● Quantifying the cost of poor performance ● Using statistics to summarize baseline performance ● Using Pareto charts ● Using variation plots Apply for this course //

In many ways Kanban is counterintuitive. The system relies on basic rules and practices, and these rules can help you start a large-scale organizational change. The kanban board might only appear to be a simple diagram that shows the team's workflow. But it can help build cross-functional self-organized teams, encourage better collaboration, and increase your team's productivity. Kanban is a key way to introduce lean principles in your organization. Lean can help your teams better prioritize their work and continuously improve by removing the waste or "muda" from your process. In this course, explore essential lean principles and discover how to use a kanban board to help your team prioritize more effectively. Learn about starting enterprise lean, setting up a board, optimizing your flow, and more. Apply for this course

Learn about lean: an operations management approach that means creating more value for customers with fewer resources. A lean organization understands customer value and focuses its key processes to continuously increase it. The ultimate goal is to provide perfect value to the customer through a value creation process that has zero waste.Lean concepts have been successfully applied to every aspect of doing business. In this course, learn the principles of lean and how they are used in processes, production, and services. Instructor Steven Brown also explains how lean thinking impacts the organization, from the overall business culture to day-to-day work activities. Topics include:● What is lean? ● Process mapping and reengineering ● Cost and constraints ● Lean manufacturing ● Lean services ● Lean culture ● Lean thinking Apply for this course //

Lean Six Sigma combines the principles of lean enterprise and lean manufacturing with Six Sigma to improve performance and systematically remove waste. Supply chain expert and professor Steven Brown explains the basics of using Lean Six Sigma as a structure for your improvement efforts.Steven outlines the process stages in Six Sigma (define, measure, analyze, improve, and control), along with the Lean toolkit: the 5s principles, kanban (scheduling), downtime, poka-yoke (error proofing), and kaizen (continuous improvement). He also explains how leadership works within Lean Six Sigma, the principles of project execution, and how Lean Six Sigma is applied to the service sector and supply chain management. Make sure to watch the "Next steps" video at the end of the course for further resources. Apply for this course

You have a great idea you believe will improve your business. In order to make your idea a reality, you may be asked to write a business case that clearly articulates what you want to accomplish, how you're going to do it, and why it's worth doing. Business cases are traditionally used in approval and prioritization processes. They can also be used to measure the results of an initiative. In this course, join Mike Figliuolo as he explains step-by-step how to craft a compelling business case for your stakeholders. Mike covers how to define the problem your plan addresses, communicate your idea's benefits, build the financial projections to support your case, create a robust risk assessment, and more. Learning objectives Define the structure and uses of a business case. Write effective executive summaries. Explain the components of a problem definition. Describe how to articulate the benefits of an idea. Estimate financial results and identify measurements of success. Describe how to outline risks and opportunities. Create milestones. Apply for this course

In this learning path, you can learn all the skills to gather, document, and analyze business needs and requirements and become a successful business analyst. Develop basic business analyst skills required for this role. Demonstrate technical skills to execute effectively. Build leadership and communication skills to excel and advance. Apply for this course

One of the main reasons given for unsuccessful project results is the lack of clear understanding of stakeholder requirements. Business analysis helps to prevent project failure by identifying and validating those requirements early on. Of course, business analysis doesn’t stop with requirements; business analysts also recommend solutions and facilitate their execution. This course provides an introduction to the foundations of business analysis. It helps demystify the role of the business analyst (BA), and outlines the knowledge and skills required to build a successful BA career. Instructor Greta Blash also provides an in-depth review of the business analysis process, from conducting a needs assessment and identifying stakeholders to testing, validation, and release. Each lesson demonstrates why business analysis works—and how you can use it to improve your organization. Apply for this course

In a business environment where complexity and change are the norm, business analysts and project managers can collaborate together to get more successful results and better business outcomes. If you're a PM or BA, this course will help you understand what great collaboration looks like. Explore exactly what each role entails, and what the ideal partnership can achieve. Discover how BAs and PMs can collaborate at each stage of a project, from scope management and project planning to implementation. Then find out where the roles and responsibilities overlap, and learn how to coordinate on these tasks to enhance communication, reduce risk, engage stakeholders, and more effectively respond to change requests. Apply for this course

When you're trying to grapple with user demands and market changes, it can be difficult to mentally zoom out and assess your organization's operations. Business process modeling helps you see the big picture by allowing you to translate your business processes into easily understood pictures. In this course, instructor Haydn Thomas walks you through the most widely used business process modeling diagrams—context, functional flow, cross-functional flow, and flowchart—and explains the purpose of each one. As Haydn touches on each modeling technique, he shares its unique features, explains how to use that technique to create a diagram, and points out how to avoid common pitfalls. He pulls it all together by comparing process diagrams so you can select the right one for your organization. Apply for this course

Interviews can be an effective component in identifying requirements during project planning, and help business analysts and project managers understand the project from the user's point of view. This course covers interview techniques that can help build relationships with project stakeholders and obtain accurate information about project needs. Author Angela Wick helps you identify when to use interviews, who to interview, and how to plan, conduct, and follow up on interviews. Apply for this course

Learn how to create, edit, format, and share documents with ease using the Office 365 version of Word. Follow along with David Rivers as he shows all the essential features of this powerful tool. This course covers how to edit and format text to create a stylish document with instant purpose; create numbered and bulleted lists; work with columns and tables; add images and shapes to your documents; collaborate on documents with your team; and share documents via OneDrive and email. Plus, discover how to use the proofing tools in Word to check spelling and grammar, get word counts, and more. Apply for this course

Microsoft SharePoint Online is a significant component of Microsoft 365 teamwork solutions. In this course, Ed Liberman shows how to configure and manage SharePoint Online, including how to plan and configure site collections and apps. Ed also demonstrates how to customize sites within SharePoint using apps, manage user profiles, create relevant search results for users, and monitor and maintain the SharePoint Online service. Apply for this course

You don't have to be a designer to create a great-looking presentation. Learn how to use Microsoft PowerPoint for Office 365 to quickly create, edit, and share professional-looking presentations. In this training course, Jess Stratton shows how to get started with PowerPoint templates and themes or build a new presentation from scratch. She explains how to change the slide layout; add and edit text, images, charts, video, and animation; format slides for consistency; and add speaker notes and comments to ensure a smooth delivery. Plus, discover how to collaborate on changes and share presentations with others. By the end of the course, you'll know how to use the PowerPoint tools and follow a few simple design rules to draw attention to your message and deliver a presentation that shines. Apply for this course

Microsoft Project has an almost overwhelming number of features. How do you understand everything it can do? This tips-based course shows you how to get the most out of Microsoft Project, sharing time-saving tricks, powerful shortcuts, and reviews of cool hidden features. Bonnie Biafore shares techniques to increase your expertise, boost your productivity, and coax Project to do exactly what you want. Learn to create hammock tasks, prevent duplicate resources, create new views, summarize resource utilization, and more. Check back every Tuesday for a new tip. To suggest a tip for Bonnie to cover in the future, submit course feedback. Note: Because this is an ongoing series, viewers will not receive a certificate of completion. Apply for this course

Building on the skills learned in the popular Project 2010 and Project 2013 Essential Training courses, author Bonnie Biafore teaches more advanced aspects of the popular project management software, first introducing powerful shortcuts for opening and saving files, and then moving into assigning resources, managing project costs, and setting up earned value tracking. She also provides handy tips for exchanging data with other projects as well as linking and embedding data. Viewers will then learn how to customize fields and generate cool graphical and visual reports. Finally, the course shows how to share various customizations and configurations as well as best practices for managing multiple projects. Apply for this course

Master the core features of Microsoft® Project 2016, the powerful project management software. Learn how to best set up such project components as work tasks, summary tasks, milestones, and recurring tasks. Author Bonnie Biafore, a Project Management Professional (PMP)®, also explores the different types of resources used in projects, and how to set up their availability and cost. She also shows how to link tasks together and assign resources to tasks to build a realistic project schedule. Finally, the course explains how to use Project 2016 to help evaluate your schedule and resource workloads to make sure you're bringing a project in on time and within budget. Bonnie also shows how to use the new features in Project 2016, such as multiple timelines and the "Tell me what you want to do" field. NOTE: This course updates our Microsoft Project 2013 Essential Training course for Project 2016, and most videos will work with both versions of the software. For Microsoft Project 2010 compatibility, see Project 2010 Essential Training. Apply for this course

Get up to speed with Microsoft Excel, the world's most popular spreadsheet program. Follow along with Excel expert Dennis Taylor as he demonstrates how to efficiently manage and analyze data with this powerful program. Learn how to enter and organize data, perform calculations with simple functions, and format the appearance of rows, columns, cells, and data. Other lessons cover how to work with multiple worksheets, build charts and PivotTables, sort and filter data, use the printing capabilities of Excel, and more. Apply for this course

Problem management is about preventing and resolving the problems underlying interruptions of IT services. A set of shared techniques can make the difference between success and failure. ITIL® mentions a set of techniques as best practice, but does not cover how to apply them. This course bridges the gap for IT pros, giving them a concise introduction to the seven problem management techniques endorsed by ITIL, including: Brainstorming Ishikawa diagrams Kepner-Tregoe root cause analysis Fault tree analysis Component failure impact analysis Service outage analysis Post-implementation and major problem review Apply for this course

This installment of the Putting ITIL® into Practice series helps ITIL® Foundation certified professionals get a practical start at applying DevOps concepts within their ITIL®-driven enterprise IT organizations as they move from traditional IT towards cloud and mobile on their journey of digital transformation. Throughout this course, instructor David Pultorak examines where DevOps and ITIL® Foundation concepts intersect in an enterprise setting. He begins by introducing DevOps for ITIL®-driven shops, including a discussion of what cloud-native DevOps and enterprise IT shops do and do not have in common. He then covers ideas on how to adapt DevOps values, principles, methods, practices, and tools to accommodate enterprise IT challenges; how to adapt each of the aspects of ITIL®-driven shops to accommodate DevOps values, principles, methods, practices, and tools. Topics include: What DevOps and enterprise DevOps have in common DevOps and enterprise IT challenges Enterprise-level change control and release gates DevOps values, principles, and methods ITIL®-driven shops and DevOps Reviewing the service lifecycle Strategy, design, operations, and CSI processes Technology and architecture Apply for this course

The release of ITIL® 4 modernizes the popular service management framework, adding coverage of topics such as lean, agile, and DevOps. In this course, get a first look at the ITIL® 4 Foundation exam. ITIL® Expert David Pultorak provides a high-level overview of ITIL® 4, as well as how updates to the framework affect the ITIL® Foundation certification exam. Learn about the similarities and differences between the ITIL 4® and ITIL® v3 Foundation exams and certification schemes, as well as what sparked the creation of ITIL® 4 in the first place. Plus, explore the seven guiding principles of ITIL® 4, the four dimensions of service management, the components of the ITIL® 4 service value system, and more. Apply for this course

In today’s big-data world, understanding how to model phenomena with a relational database is an invaluable skill. A variety of different users—from government agency employees to gamers—rely on relational databases for everyday operations. In this course, join Adam Wilbert as he covers the fundamentals of the relational model for creating databases of real-world situations. Adam goes over concepts that are applicable to a wide variety of platforms, including SQL Server, Oracle, Access, MySQL, and PostgreSQL. Learn the basics of data storage, review the structure of a data table, and learn how to plan your relational database using an entity-relationship design tool. Plus, explore data integrity and validation, table relationships, writing queries, and more. Learning objectives The basics of data storage Choosing an entity-relationship design tool Using primary keys to identify records What to consider when naming objects Creating a unique constraint Establishing table indexes Relating tables with foreign keys One-to-many and one-to-one relationships Normalization Writing SELECT queries in SQL Apply for this course

Have you ever opened up a database that someone else built and felt a little lost? Or ever thought of designing your own simple database and been unsure of where to start? Or perhaps you need to work with a team of database professionals and don't know how to speak their language? This course can help you overcome these hurdles.Adam Wilbert covers the basics of relational database design, regardless of whether you use Access, FileMaker, Open Office, or SQL Server. Learn how to prevent data anomalies, gather requirements to plan your design, and develop a conceptual data model—translating your ideas into components like tables, relationships, queries, and views. Plus, learn about logical design considerations that can help you construct a database that is easy to maintain. Learning objectives Identify the three rules of relations. Summarize the four stages of developing a relational database. Describe a strategy one might use to ensure a database remains flexible in terms of the questions a user can ask. Explain how to avoid scope creep. Recall the characteristics of a Lookup Table. Recognize situations in which denormalization would be beneficial. Understand the types of relationships modeled by junction tables. Define referential integrity. Apply for this course

Get up and running with Oracle Database 19c, the latest version of the popular relational database management system (RDBMS), and learn how it can help enhance your database design and deployment process. Throughout this course, instructor Bob Bryla covers the fundamentals of administering Oracle Database 19c. Discover how to install the RDBMS on Linux, manage the database and query tables using the SQLcl command-line tool, and efficiently move data in and out of your database tables using SELECT and DML statements, respectively. Plus, learn how to create, assign, and drop tablespaces, as well as how to create and drop user accounts. Apply for this course

Ongoing, regular administration is critical to the security and performance of databases such as Oracle and SQL Server. It's also a key topic of the Microsoft Technology Associate (MTA) Exam. Whether you're studying to pass the test or simply to keep your admin skills up to date, this course will cover the most current techniques and best practices for administering a database. Adam Wilbert covers the core concepts, including securing the server with user authentication and roles, assigning object-level permissions, and performing a backup and restore. Along the way, he'll provide tips for working with SQL Server Management Studio and some challenges to help you practice what you've learned.Note: This course will also prepare certification candidates for the "Administer a database" domain of the Microsoft Technology Associate (MTA) Exam 98-364, Database Administration Fundamentals. Apply for this course

Data science is driving a world-wide revolution that touches everything from business automation to social interaction. It’s also one of the fastest growing, most rewarding careers, employing analysts and engineers around the globe. This course provides an accessible, nontechnical overview of the field, covering the vocabulary, skills, jobs, tools, and techniques of data science. Instructor Barton Poulson defines the relationships to other data-saturated fields such as machine learning and artificial intelligence. He reviews the primary practices: gathering and analyzing data, formulating rules for classification and decision-making, and drawing actionable insights. He also discusses ethics and accountability and provides direction to learn more. By the end, you’ll see how data science can help you make better decisions, gain deeper insights, and make your work more effective and efficient. Apply for this course

Trying to choose a tool to perform software testing? The market is a minefield, full of so many choices that it becomes difficult to zero in on the best tool for your unique test environment. This course surveys the most popular software testing tools available, including paid and open-source solutions such as Selenium, Postman, JMeter, and Kali Linux. Instructor Michael Smith—an experienced tester and software architect—breaks down the tools according to their suitability for each discipline, including API testing, security testing, load testing, and more. He also covers tools for lifecycle management and test planning, and dives into areas beyond the traditional software testing role, including unit and infrastructure testing. This review helps you narrow down your choices and understand the pros and cons of each platform, so you can make the right additions to your testing toolkit. Apply for this course

As software companies continue to shift towards cloud computing, mobile apps, and microservice architectures, the ability to quickly and effectively test APIs has become a critical skill for software testers. In this course, instructor Dave Westerveld covers the basics of API testing, sharing how to work with several robust tools for testing APIs at scale in an organization. After providing a primer on web services and important API terminology, Dave shows how to use Postman for some basic API exploration. He then goes over some basic approaches and methodologies used in testing GET, POST, PUT, and DELETE requests; shows how to approach performance testing using SoapUI, a popular automated API testing tool; and more. Apply for this course

Agile is an exciting way to quickly deliver higher-quality products to your customer. New agile tools are emerging every day. This course helps you compare the strengths and capabilities of several different agile software tools, including Microsoft Excel, Atlassian JIRA, VersionOne, Microsoft Team Foundation Server (TFS), CA Agile Central (formerly Rally), and Agility Health. You'll see the advantages of simple tools like spreadsheets versus more complex solutions like complete product management packages. This course helps project managers, software developers, and other professionals determine which tool is the best fit for their team. Agile expert Doug Rose provides a fast-paced tour and an unvarnished look at what some of the tools get right and what some get wrong. Doug concludes each section with suggested strategies for selecting the right tool for your team—always remembering that no tool should ever overshadow the core values outlined in the agile manifesto. Apply for this course

Agile teams need a lightweight way to report their progress. Agile reports should be simple and easy to read, and radiate information across the room to the entire team. In this course, agile expert Doug Rose outlines a process for reporting on the progress of your agile project. He shows how to establish priorities using product backlogs, show daily progress using taskboards, burn down a sprint using sprint burndown charts, and burn down a release by creating a release burndown chart. He also highlights common pitfalls, such as retrofitting. Bonus: Watch the bonus chapter at the end of this course where Doug answers common questions about the agile mindset, including what types of projects would be the best fit.Topics include: Communicating progress Prioritizing the backlog Showing daily progress with a taskboard Sizing taskboards Creating a burndown chart Apply for this course

Designed to help increase the pace and quality of a team’s work, agile retrospectives utilize a structured format to gather insights, identify challenges, create a more agile mindset, and make a team more productive and successful. Author Doug Rose outlines the five phases of a successful retrospective: setting the right direction, getting all the issues on the table, gathering insights from the team, making decisions, and applying changes. He describes how to use a starfish diagram or PANCAKE approach to facilitate a comfortable and effective retrospective, and finally, discusses the importance of closing a retrospective with clear action items for the next sprint. Apply for this course

Many new agile teams think flexibility in their meetings allows them to do whatever feels right. In reality, agile projects move more smoothly by running short, well-structured activities. Each activity is timeboxed, so the teams stay on track and work within a set time and agenda. In this course, agile expert Doug Rose outlines how to make agile meetings as productive as possible. He provides guidance on common activities such as release planning, daily stand-ups, sprint planning, and product demos. Throughout the course, learn about common meeting pitfalls and the challenges of keeping activities on track. To learn more about agile, watch additional courses in the Agile at Work series. Apply for this course

Agile project teams create short user stories as a way to plan out the work for upcoming sprints. In this course, agile expert Doug Rose shows how to write these user stories and prioritize them in the product backlog. He also shows how to avoid the most common pitfalls with agile project planning. Apply for this course

Agile project teams create short user stories as a way to plan out the work for upcoming sprints. In this course, agile expert Doug Rose shows how to write these user stories and prioritize them in the product backlog. He also shows how to avoid the most common pitfalls with agile project planning. Apply for this course

Is your organization looking to realize the time, quality, and cost benefits of agile project management? If so, then this course is for you. Join project management trainer and agile expert Kelley O'Connell as she helps those interested in experimenting with agile understand the difference between traditional waterfall and agile methodologies, as well as what's required for success. Kelley provides advice on how to garner support for your pilot project by identifying supporters early on and keeping them engaged while also responding to detractors. She then leads you through the process of picking a pilot project, choosing the right team, and setting the vision. To wrap up, Kelley provides a short overview of agile basics—including how to approach sprint planning—to help you get started. Apply for this course

Teams that embrace an agile mindset are often better able to respond to customer feedback and shifting business needs—and have a bit more fun in the process. Interested in bringing the principles of agile to your team? This course can help. Join Doug Rose as he steps through the fundamental concepts you need to know to start thinking like an agile team. Doug goes over the values and principles covered in the agile manifesto, as well as how to enhance communication with user stories and cross-functional teams. Discover how to respond to change the agile way, explore popular agile frameworks, and learn about the common roles on an agile team. Along the way, Doug provides you with some exercises that can help boost your team's agility and productivity. Apply for this course

Deliver projects with the highest level of performance and quality as an agile project manager. This path will help you build a solid foundation in leading and motivating agile project teams, from developing user stories and agile charts to driving productive meetings. Apply for this course

APIs are a crucial business driver for delivering data to your applications. In this course, learn about various options for securing your RESTful API that can help you keep your application data—and your users—safe. Instructor Emmanuel Henri begins the course with an overview of top security threats and an introduction to the Open Web Application Security Project (OWASP), an important resource on security. He then steps through how to set up and secure a Node and Express API, including how to add handlers for registration and login, finalize secured endpoints, and test your finalized API. To wrap up, he shares a few alternatives for securing APIs. Topics include: Open Web Application Security Project (OWASP) Reasons for using a JSON Web Token (JWT) Adding bcrypt password hashing Adding handlers for registration and login Finalizing secured endpoints Testing APIs with Postman Apply for this course

Learn how to use Git, the popular open-source version control software, to manage the source code for almost any project. In this course, Kevin Skoglund explores the fundamental concepts behind version control systems and the Git architecture. Using a step-by-step approach, he shows how to install Git and presents the commands that enable efficient code management. Learn how to add, change, and delete files in the repository; view a log of previous commits; and compare versions of a file. Plus, see how to undo changes to files and ignore certain files in a Git repository. Topics include: Exploring the history of version control Installing Git on Mac, Windows, and Linux Initializing a repository Writing useful commit messages Understanding the Git three-tree architecture Tracking when files are added, edited, deleted, or moved Viewing change sets and comparing versions Undoing changes and rolling back to previous versions Ignoring changes to select files Apply for this course

PHP is still one most popular server-side languages used to build dynamic websites, powering everything from Facebook to Wikipedia. And although it is not especially difficult to use, nonprogrammers often find it intimidating. This introductory course was designed to change that by teaching you PHP through a series of clear, focused, and easy-to-follow lessons. After briefly explaining what PHP is, instructor Joe Casabona introduces the features of the language. He covers variables, control structures, calculations, loops, and functions, as well as includes and error handing, in a series of hands-on exercises. He then moves on to more advanced topics, including how to maintain state with sessions and cookies. Upon wrapping up this course, you'll have the skills you need to start developing and maintaining interactive websites using PHP. Topics include: Naming variables Storing text as strings Doing calculations with PHP Using conditional statements to make decisions Creating custom functions Deciphering error messages Emailing the contents of an online form Dealing with multiple-choice form fields Apply for this course

Do you rely on IT to get the data you need? Are you often stuck waiting in line for data, and wish you could just retrieve it yourself? In this course, learn how to get the data you want by writing a bit of SQL code. You won't just be able to pull data out of the database; you'll be able to manipulate it: merging it, grouping it, and relabeling it to get just the report you want. Join Emma Saunders as she shows how to write simple SQL queries for data reporting and analysis. Learn how to filter, group, and sort data, using built-in SQL functions to format or calculate results. Discover how to perform more complex queries, such as joining data together from different database tables. Last but not least, she introduces views, procedures, functions, and variables. Topics include: Retrieving data with SELECT statements Filtering and sorting your results Transforming results with built-in SQL functions Grouping SQL results Merging data from multiple tables Using variables, functions, and procedures Apply for this course

Understand the core concepts every IT professional should know to start working with databases. This course, the first in a four-part series with database consultant Adam Wilbert, is designed to provide a solid foundation that will serve you throughout your IT career. Learn about the different data storage models and find out how to build your first database with SQL Server—the Express edition, which requires no hardware or special connections for setup. Then discover how to create database objects with the data definition language (DDL) and edit data in your tables with data manipulation language (DML). Adam also covers critical relational database concepts, such as relationships, indexes, and schemes.Note: This course will also prepare certification candidates for the Microsoft Technology Associate Exam 98-364, Database Administration Fundamentals. Apply for this course