5 Free Courses to Master Data Science

Want to break into data science? Start upskilling today with these free courses to learn programming, data analysis, and machine learning.

5 Free Courses to Master Data Science
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Are you an aspiring data professional looking to kickstart your data science career? If so, you’re probably considering various options: online courses, bootcamps, master’s degree, and more.

But if you are motivated enough, there are several high-quality free resources that can help you get there. Here, we’ve compiled a list of five such free courses that can help you learn and gain proficiency in data science.

From programming fundamentals to building and deploying data science applications, these courses will teach you everything you need for a successful career pivot. 

Let’s dive right in!


1. Python for Everybody


Python for Everybody, taught by Prof. Charles Severance at the University of Michigan is a great course to learn Python. It teaches you Python Programming from the ground up—covering everything you need to know when working with data.

You can also use the Python for Everybody book in conjunction with the course. The course covers the following broad topics:

  • Programming fundamentals with Python 
  • Python data structures 
  • Conditional execution, loops and iteration
  • Functions
  • Regular expressions
  • Web services and networked programs 
  • Data visualization

Course link: Python for Everybody


2. Data Analysis with Python


Now that you have your Python fundamentals down, it’s time to analyze data with Python. Data analysis with Python from Jovian (on freeCodeCamp's YouTube channel) is a free course that’ll help you learn to work with data science libraries with several practice exercises and a course project. 

This course starts out with Python Programming fundamentals (which should be a refresher for you) and gradually introduces Python data analysis libraries. And wraps up with an end-of-course project on exploratory data analysis.

Here’s an overview of the course curriculum:

  • Python fundamentals 
  • Numerical computing with NumPy
  • Analyzing tabular data with pandas
  • Visualization with Matplotlib and Seaborn
  • Course project: Exploratory Data Analysis

Course link: Data Analysis with Python


3. Databases and SQL


Introduction to Databases in Data Science outlines the essential database skills for data professionals.

From designing databases to writing efficient SQL queries and more, databases and SQL are must-have skills for your data career. This Databases and SQL course from freeCodeCamp will teach you the following:

  • Database fundamentals 
  • SQL basics 
  • CRUD operations
  • Functions, joins, and unions
  • Nested queries 
  • Designing database schema

Course link: Databases and SQL


4. Intro to Inferential Statistics


Aside from high school math—Calculus, Probability, and Linear algebra—you need to have a strong foundation in statistics to excel in data science.

Intro to Inferential Statistics from Udacity’s free course library will teach you the following concepts—along with coding exercises to test your skills:

  • Estimation
  • Hypothesis Testing
  • t-Tests
  • Chi-Squared Test
  • Correlation
  • Regression

Course link: Intro to Inferential Statistics


5. Machine Learning Zoomcamp


The courses listed thus far should have helped you gain proficiency over Python fundamentals, data analysis, and statistics foundations.

Now it's time to start building and deploying machine learning models. Machine Learning Zoomcamp by DataTalks.Club is a great course to learn the fundamentals of machine learning through a code-first approach. It also covers a good breadth of topics  including model deployment and deep learning.

The course curriculum includes the following:

  • Regression 
  • Classification 
  • Evaluating machine learning models
  • Deploying machine learning models 
  • Decision trees and ensemble learning 
  • Neural networks and deep learning 
  • Kubernetes and TensorFlow Serving

Course link: Machine Learning Zoomcamp


Wrapping Up


I hope you found these recommended courses helpful. Most of these courses require you to code, build, break, and learn along the way. So you’ll have a good foundation. 

But even as you're working through these courses, build your portfolio on the side. Your goal should be to build a handful of interesting projects that showcase your strength and skills. If you need some inspiration to get started, check out 3 Data Science Projects Guaranteed to Land You That Job. Happy learning!

Bala Priya C is a developer and technical writer from India. She likes working at the intersection of math, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She enjoys reading, writing, coding, and coffee! Currently, she's working on learning and sharing her knowledge with the developer community by authoring tutorials, how-to guides, opinion pieces, and more.