Free Data Analytics Courses You Must Know in 2021

Naveen Jujaray
4 min readAug 12, 2021


Time to Complete — 6 Weeks

This is a completely free course and a good first step towards understanding the data analysis process. In this course, you will learn the entire data analysis process, including posing a question, data wrangling, exploring the data, drawing conclusions, and communicating your findings. This course will also teach Python libraries NumPy, Pandas, and Matplotlib.

You Should Enroll if-

  • You are comfortable with Python programming.


Time to Complete- 5hr 9min

This is another completely free data analysis course. In this course, you will learn the components of the two primary pandas objects, the DataFrame and Series. In this course, all material and exercises are written in Jupyter Notebooks, which you can download.

But this course doesn’t cover all of the pandas library. This course covers only a small and fundamental portion of it. This course is good to understand the deep introduction to subset selection of a DataFrame or Series.

You Should Enroll if-

  • You understand the fundamentals of Python.

3. SQL for Data Analysis– UDACITY

Time to Complete- 4 weeks

This course is completely free and covers SQL to extract and analyze data stored in databases. SQL is used to perform data analysis in this course. First, you will learn SQL basics like how to extract data, SQL joins to join tables and SQL aggregations.

Then you will learn how to perform complex analysis and manipulations using subqueries, temp tables, and window functions.

You Should Enroll if-

  • You have general familiarity working with data in spreadsheets.

4. Bayesian Statistics: From Concept to Data Analysis– COURSERA

Time to Complete- 12 hours

This is a Free to Audit course offered by the University of California, but this course is not for beginners. This course begins with the basics of probability and Bayes’ theorem. Then covers the concepts of statistical inference from both frequentist and Bayesian perspectives.

After that, you will learn methods for selecting prior distributions and building models for discrete data. And in the last, this course covers the conjugate and objective Bayesian analysis for continuous data.

You Should Enroll if-

  • You should have prior knowledge of basic statistics class (for example, probability, the Central Limit Theorem, confidence intervals, linear regression) and calculus (integration and differentiation).

5. Data Analysis with R– UDACITY

Time to Complete- 2 Months

This is an intermediate-level free course to learn data analysis using R programming. This course begins with the introduction of exploratory data analysis (EDA). Then you will learn R basics by installing RStudio and packages.

After that, you will perform EDA to understand the distribution of a variable and to check for anomalies and outliers. You will also learn how to quantify and visualize individual variables within a data set to make sense of a pseudo-data set of Facebook users.

In this course, you will work on the Diamonds and Price Predictions project. In this project, you will investigate the diamond data set and see how predictive modeling can allow us to determine a good price for a diamond.

You Should Enroll if-

  • You have prior knowledge of statistics.

6. Exploratory Data Analysis in Python– DATACAMP

In DataCamp, full courses are not free. Only the first lesson of all courses is free. Similarly, in this course, you will get access to its first lesson free of cost. So, in the first lesson of this course, you will learn how to read the data, how to check for errors and special cases, and how to prepare data for analysis.

You Should Enroll if-

  • You have prior Python knowledge.

7. Data Analysis and Visualization– UDACITY

Time to Complete- 16 Weeks

This is another free course for learning data analysis and visualization. In this course, you will understand the different techniques and theories behind data analysis and visualization. You will also learn how to write programs and scripts that analyze and visualize the data.

R programming language is used in this course. In this course, you will also learn how to model data using logistics regression and linear regression. At the last of this course, you will learn how to handle high-dimensional data effectively using regularization.

You Should Enroll if-

  • You have prior programming experience and are familiar with mathematics (basic linear algebra, calculus, introductory probability).

8. Python for Data Analysis– UDEMY

Time to Complete– 1hr 10min

In this free data analytics course, you will learn how to combine your existing knowledge of Python with tools like Pandas and Numpy. Throughout this short course, you will learn the most commonly used tools for data analysis with python including JupyterLab, Numpy, and Pandas. And you will also learn how to create visualizations from your data using Matplotlib and Seaborn.

You Should Enroll if-

  • You have prior knowledge of Python programming.

That’s all!

These are the 8 Best Free Online Data Analytics Courses. Now, it’s time to wrap up.


I hope these 8 Best Free Online Data Analytics Courses will help you to learn data analytics. My aim is to provide you the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Happy Learning!