Statistics & Data Analysis

 


 

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E.g., 2017-09-20
E.g., 2017-09-20
E.g., 2017-09-20
Nov 1st 2017

Once, only cartographers made maps. Today anyone can. Still, cartographers can teach people to make better maps, just as chefs can show people how to cook better meals. With coaching from experienced cartographers and practical, hands-on exercises using ArcGIS Pro, you'll become a smarter mapmaker, ready to go beyond the defaults and make better maps.

Average: 3 (4 votes)
Oct 2nd 2017

Understand how randomized evaluations can be used to evaluate social and development programs. Learn why evaluations matter and how they can be used to rigorously measure the social impact of development programs. This practical course will provide a thorough understanding of randomized evaluations, with pragmatic step-by-step training for conducting one’s own evaluation.

Average: 1.3 (3 votes)
Self Paced

Learn best approaches and practices for marketing measurement, including how to use metrics to measure success. Begin your journey in a new career in marketing analytics. Learn about powerful strategies and methodology, starting with identifying market trends and metrics used to measure marketing success. In this marketing course, you will learn how to execute market sizing, identify market trends, and predict future conditions.

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Oct 2nd 2017

This course is a hands-on introduction to statistical data analysis that emphasises fundamental concepts and practical skills.

Average: 5.7 (3 votes)
Self Paced

Learn Power BI, a powerful cloud-based service that helps data scientists visualize and share insights from their organizations’ data. Power BI is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations’ data.

Average: 6.5 (4 votes)
Self Paced

Get hands-on experience building and deriving insights from machine learning models using R, Python, and Azure Machine Learning. Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.

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Self Paced

Explore data analysis and visualization in Excel, the cloud benefits of Power BI, and Power Pivot, pivot tables, and tools previously known as Power Query. Microsoft Excel is one of the most widely used solutions for analyzing and visualizing data. Beginning with Excel 2010, new tools were introduced to enable the analysis of more data, resulting in less time spent creating and maintaining the solutions and enabling a better understanding of what the data means. This better understanding is facilitated by improved visualizations and more sophisticated business logics.
Do you want to take your advanced Excel skills to the next level? Are you exploring new ways to get and transform your data and create visualization?

Average: 4.7 (18 votes)
Self Paced

Learn the R statistical programming language, the lingua franca of data science. R is rapidly becoming the leading language in data science and statistics. Today, the R programming language is the tool of choice for data scientists in every industry and field. Whether you are a full-time number cruncher, or just the occasional data analyst, R will suit your needs.

Average: 6.5 (6 votes)
Self Paced

The ability to analyze data with Python is critical in data science. Learn the basics, and move on to create stunning visualizations.

Average: 6.1 (15 votes)
Self Paced

Learn how to use Hadoop technologies in Microsoft Azure HDInsight to create predictive analytics and machine learning solutions. Are you ready for big data science? In this course, learn how to implement predictive analytics solutions for big data using Apache Spark in Microsoft Azure HDInsight. You will learn how to work with Scala or Python to cleanse and transform data, build machine learning models with Spark MLlib (the machine learning library in Spark), and create real-time machine learning solutions using Spark Streaming. Plus, find out how to use R Server on Spark to work with data at scale in the R language.

Average: 7.3 (4 votes)
Self Paced

Learn the basics of Excel, one of the most popular data analysis tools, to help visualize and gain insights from your data. The ability to analyze data is a powerful skill that helps you make better decisions. Microsoft Excel is one of the top tools for data analysis and the built-in pivot tables are arguably the most popular analytic tool.

Average: 4.5 (2 votes)

Self Paced

Gain a solid understanding of statistics and basic probability, using Excel, and build on your data analysis and data science foundation. If you’re considering a career as a data analyst, you need to know about histograms, Pareto charts, Boxplots, Bayes’ theorem, and much more. In this applied statistics course, the second in our Microsoft Excel Data Analyst XSeries, use the powerful tools built into Excel, and explore the core principles of statistics and basic probability—from both the conceptual and applied perspectives.

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