Improve your analytics skills with 10 free courses


Improving your analytics capabilities is always a good investment. The ability to conduct robust data analysis, tell stories with data, and understand the importance of advanced data science technology such as machine learning can make you invaluable within any organization.

1. IBM’s Introduction to Data Science

New to data science? IBM’s Introduction to Data Science course covers the essentials of data science, such as what data science really is, what data scientists do, essential skills, and how to build a data science team from the ground up.

2. HarvardX’s Data Science: R Basics

As a specialized, open-source programming language, R is designed for statistics and data analysis. While it isn’t a general-purpose language like Python, R is fantastic for conducting complex data analysis such as machine learning and statistical analysis.

In HarvardX’s Data Science: R Basics course, you’ll learn the fundamental functions of R by solving real-world problems, understanding R syntax, and performing operations.

3. IBM Python Basics for Everyone

Python is one of the most popular programming languages in the world because of its versatility and easy syntax. It is not only used for data science but also in web development. Python is generally easier to learn for beginners in data science because its syntax is logical and approachable. If you are interested in building data structures or pipelines, consider learning Python basics with IBM’s Python Basics for Everyone.

This course is a beginner-friendly introduction to Python programming that allows you to perform data analysis in their virtual lab environment.

4. UBCx’s Excel for Everyone: Core Foundations

Excel can perform surprisingly powerful data analysis. It’s also considered one of the most popular spreadsheet tools in the world, meaning that if you can master Excel, you’ll be learning a valuable skill.

In UBCx’s Excel for Everyone: Core Foundations, you’ll gain exposure to data wrangling, spreadsheet wrangling, and analysis.

5. Columbia University Statistical Thinking for Data Science and Analytics

The foundation of quantifying, interpreting, and visualizing big data is statistics. “Statistics tells this story of how to describe what the data looks like or how these two things relate to each other or this is the trend, and this is what we can anticipate in the future,” said Gwen Britton. “Each of those different things has an underlying story behind it that is really based on statistics.”

In Columbia University’s Statistical Thinking for Data Science and Analytics, you’ll get a sense of how data scientists use statistical thinking to collect data, derive insights, and build predictive models. 

6. HarvardX’s Introduction to Probability

In data science, predictive analytics and forecasting heavily rely on probability. Probability is part of a subset of statistical techniques data scientists use to figure out the chance that something will occur. This skill is critical to have, especially when making significant business decisions.

If you’re interested in improving your predictive capabilities, HarvardX’s Introduction to Probability course will introduce you to core probability concepts such as statistical inference, randomized algorithms, and more.

7. IBM’s SQL For Everybody

To conduct data analysis, you first need to be able to pull the correct data, and SQL is a powerful tool that does just that. With SQL, you can surface or manipulate data from databases. For those interested in pursuing a career as a data or business analyst or who want to visualize data with tools like Tableau properly, SQL is a must-have skill to improve your data analysis abilities.

With IBM’s SQL for Everybody, you’ll use SQL to work with databases, run SQL queries, and even create your own database.

8. University of Michigan’s Introduction to Data Analytics for Managers

Understanding how to source and interpret data is critical to helping people in management roles make decisions and develop business strategies. For aspiring or current managers in business who want to develop a background in data analytics, the University of Michigan’s Introduction to Data Analytics for Managers covers a broad range of case studies, hands-on learning, and lectures to introduce data analysis techniques in business applications.

9. UC San Diego’s Machine Learning Fundamentals

Machine learning is an advanced system that can gain insights from data in an automated, or self-learning, fashion. According to data from Glassdoor, many employers consider machine learning a top skill because it requires extensive knowledge in several complex domains like mathematics, programming, and computer science.

Explore machine learning with UC San Diego’s Machine Learning Fundamentals course.

10. Davidson’s Analyzing and Visualizing Data with PowerBI

Whether you’re a marketing analyst, seasoned academic, or a student, knowing how to visualize data results is pivotal. In DavidsonX’s Analyzing and Visualizing Data with PowerBI, you’ll learn how to tell stories with data visualizations with one of the most popular data science tools today.


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