Interestingly, there has been a rapid upsurge in the number of people taking up free online courses during the COVID-19 pandemic. Popular platforms like Coursera, edX, Datacamp, Udacity, and Udemy, among others, have made their courses accessible for a limited period for people to upskill themselves. Data science is among the most popular picks among online learners. There has been a huge demand for the best data science courses from the best platforms.

We have handpicked some of the most trending free data science courses for you. Most of these courses are auditable, meaning you can access them for free but would need to pay some amount to avail the certificate. Nonetheless, this is an excellent opportunity for those who were looking forward to learning data science.

The free data science courses are categorized based on their difficulty level. You can pick the one that suits your business requirements and personal aspirations. Let’s take a look.


Data Science Courses for Beginners

Introduction to Computational Thinking and Data Science by MIT (Duration – 8 weeks)

The course is designed for participants with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students write small programs. It uses Python 3.5 programming language.


Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership on Coursera (Duration – 4 weeks)

This data science courses will help you understand the end-to-end implementation of machine learning. You will learn how to avoid common management mistakes that hamper machine learning projects.

Managing, Describing, and Analyzing Data from the University of Colorado Boulder on Coursera (Duration – 5 weeks)

Understand the data and learn how to classify it correctly to make correct decisions. You will learn how to describe data both graphically and numerically using descriptive statistics and R software.

Data Science: Machine Learning from Harvard University on edX (Duration – 8 weeks)

The course will help you to learn popular machine learning algorithms, PCA, and regularization by building a movie recommendation system. Besides, you will learn about training data and how to use a set of data to discover potentially predictive relationships.

Cloud computing from IIT Kharagpur on NPTEL (Duration – 8 weeks)

The course covers different aspects of cloud computing. It includes fundamentals, management issues, security challenges, and future research trends.

CS50’s Introduction to Artificial Intelligence with Python by Harvard (Duration – 7 weeks)

This specialized course in Artificial Intelligence with Python is from Harvard. It covers modern artificial intelligence concepts and algorithms.

Artificial Intelligence Search Methods For Problem Solving from IIT Madras on NPTEL (Duration – 12 weeks)

The course discusses a wide variety of search methods that agents can employ for problem-solving.

Data Science: Machine Learning by Harvard on edX (Duration – 8 weeks)

Data Science: Machine Learning by Harvard is a part of the Professional Certificate Program in Data Science. It covers popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.

Introduction to Data Science with Google Analytics: Bridging Business and Technical Experts from Future Learn (Duration – 2 weeks)

It will offer you a platform to learn data science through Google Analytics. It helps you to analyse user behaviour and website performance. Learn how to create and use tracking codes, and view different types of data it produces.

Data Science for Engineers from IIT Madras on NPTEL (Duration -12 weeks)

It is a full-fledged course for engineers. It aims to introduce R as a programming language, mathematical foundations required for data science. The course also covers the first level data science algorithms and a data analytics problem-solving framework.

Programming for Everybody (Getting Started with Python) by the University of Michigan on Coursera (Duration – 19 Hours)

This course is part of the Python for Everybody Specialization. It covers the basics of programming computers using Python. You will learn how to create a program from a series of simple instructions in Python.

Principles, Statistical and Computational Tools for Reproducible Data Science on edX (Duration – 8 weeks)

The course is designed for students and professionals in biostatistics, computational biology, bioinformatics, and data science.

Intro to Data Science on Udacity (Duration – 2 months)

The course covers foundational topics in data science, including –

  • Data Manipulation
  • Statistics and Machine Learning
  • Data Communication
  • Working with Big Data

Introduction to Data Science – Revised by Alison (Duration – 2 – 3 Hours)

You will learn the basics of data science with this course. Get an insight into data science processes, an introduction to machine learning, and learn about data models for structuring data.

Data Science for Business Innovation by EIT Digital on Coursera (Duration – 7 Hours)

If you are a part of executive and middle-management, then this course will be helpful to you in fostering data-driven innovation. Topics cover the essential concepts and intuitions on data needs. It also covers data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Data Science: Linear Regression by Harvard University on edX (Duration – 8 Weeks)

In this course, you will learn one of the most common statistical modelling approaches in data science, which is using R to implement linear regression. There is no prerequisite to take up this course.

Linear Regression and Modeling by Duke University on Coursera (Duration – 9 Hours)

This course introduces simple and multiple linear regression models. This will help you to learn how to assess the relationship between variables in a data set and a continuous response variable.

Intro to Data Analysis via Udacity (Duration – 6 weeks)

The course will help you to explore a variety of datasets and will use Python libraries like NumPy, Pandas, and Matplotlib to understand the concepts better.

SQL for Data Science by University of California, Davis on Coursera (Duration – 14 Hours)

This course is designed for those who wish to learn about the fundamentals of SQL and working with data. You will also learn about working with different types of data like strings and numbers, and methods to filter and get insights.

Executive Data Science Specialization by Coursera (Duration – 2 months)

This program is mainly designed or business executives and leaders with no experience in data science. With this course, business leaders can understand their roles as a leader and be able to develop and work with a team.

Leaders will learn the structure of the data science pipeline, understand the goals, and develop the skills to overcome the real-world data science project challenges.

Databases and SQL for Data Science by IBM on Coursera (Duration – 15 Hours)

This course will help you to create and access a database instance on cloud, write basic SQL statements, and access databases from Jupyter using Python, among others.


Data Science Courses at Intermediate Levels

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning from on Coursera (Duration – 4 weeks)

This course will teach you the best practices for using TensorFlow, a popular open-source framework for machine learning.

Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership on Coursera (Duration – 4 weeks)

This course will help you understand the end-to-end implementation of machine learning. You will learn how to avoid common management mistake that hampers machine learning projects.

Statistical Inference and Modeling for High-throughput Experiments from Harvard University on edX (Duration – 4 weeks)

In this specialized data science course, will explore different statistics topics. These topics include multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. You will then learn statistical modelling and its application in high-throughput data.

Data Visualization with Python (Duration – 10 hours)

Data Visualization with Python will cover various techniques for presenting data visually. Apart from this, the course also covers data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium.

Data Science For Business Leaders from Altius

The course is designed for business leaders, including executives, strategists, and innovators. This course will help them to drive competitive advantage using data science.

AI Workflow: Business Priorities and Data Ingestion by IBM on Coursera (Duration – 6 Hours)

The course is a part of the IBM AI Enterprise Workflow Certification specialization. It covers the scope of the specialization and prerequisites, the concept of design thinking, and the basics of scientific thinking. You will also get to build a data ingestion pipeline using Python and Jupyter notebooks.

Fundamentals Of Artificial Intelligence from IIT Guwahati on NPTEL (Duration – 4 weeks)

With this course, you can have a basic understanding of problem-solving, knowledge representation, reasoning, and learning methods of AI. It will also offer an overview of the principles and practices of AI to address complex real-world problems.

Statistics and R on edX (Duration – 4 weeks)

The course will offer you an introduction to basic statistical concepts and R programming skills, required for data analysis in the field of life sciences.

Data Analysis with R by Facebook on Udacity (Duration – 2 Months)

The course is a part of the Data Analyst Nanodegree program. It is an approach towards summarizing and visualizing the important characteristics of a data set. You will also get to understand the data’s underlying structure and variables.

Essential Math for Machine Learning: R Edition by edX (Duration – 6 weeks)

With this machine learning course, you will learn about the essential mathematical foundations for machine learning and artificial intelligence. To complete this course successfully, you should have basic knowledge of math, along with some programming experience.

Databases and SQL for Data Science by IBM on Coursera (Duration – 15 Hours)

The course will introduce you to relational database concepts, which can help you learn and apply foundational knowledge of SQL. To take this course, you should have knowledge of SQL, Python, or programming.

Applied Data Science with Python Specialization by the University of Michigan on Coursera (Duration – 5 months)

This data science course is a series of 5 courses that would help you to gain new insights into your data. You would learn to apply data science methods and techniques and acquire analytical skills.

Data Analytics in Health – From Basics to Business on edX (Duration – 4 weeks)

The course covers the application of data analytics and big data in ensuring better diagnosis, care, and curing.

Intro to Data Science by Udacity (Duration – 2 Months)

This data science course will cover the basics of data science, including –

  • Statistics and Machine Learning for Data Analysis
  • Data Communication
  • Information Visualization
  • Working with Big Data

Getting and Cleaning Data by Johns Hopkins University via Coursera (Duration – 19 Hours)

This course will cover the basic ways to obtain data from the web, APIs, databases, and other sources in various formats. You will also learn the basics of data cleaning and ways to achieve tidy data. This course also includes the basics needed for collecting, cleaning, and sharing data.

The Data Scientist’s Toolbox by Johns Hopkins University via Coursera (Duration – 13 Hours)

This free data science course covers the basics of data analysis tools. It also covers a practical introduction to the tools for version control, markdown, git, GitHub, R, and RStudio.

Process Mining: Data science in Action by Eindhoven University of Technology via Coursera (Duration – 22 Hours)

The course will shed light on the key analysis techniques in process mining and various process discovery algorithms. It will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory across different applications.


Data Science Courses for the Experts

Google Cloud Computing Foundations from IIT Kharagpur, Google Cloud on NPTEL (8 weeks)

The course covers the basics of cloud, big data, and machine learning and its applicability to the Google Cloud Platform. 26 labs on Qwiklabs are a part of the course.

Deep Learning in Computer Vision by National Research University Higher School of Economics on Coursera (Duration – 17 hours)

This data science course is part of the Advanced Machine Learning Specialization. It covers topics like computer vision, modern deep learning models, image and action recognition, new image generation, among others.

Python for Data Science from IIT Madras on NPTEL (4 weeks)

Learn how to use python programming for solving data science problems.

Predictive Analytics and Data Mining by University of Illinois at Urbana-Champaign on Coursera (Duration – 24 hours)

This data science course is designed for businesses and managers to enable them to apply data analytics to real-world challenges. It will help them to identify the ideal analytical tools, understand valid and reliable ways to collect, analyze, visualize data, and utilize data in decision-making.

AI Workflow: Machine Learning, Visual Recognition and NLP by IBM (Duration – 7 hours)

The program is designed for existing data science practitioners with expertise in building machine learning models. It aims to sharpen the skills of building and deploying AI in large enterprises. It includes lectures and case studies focusing on natural language processing and image analysis to provide a realistic context for the model pipelines.

Statistical Inference and Modeling for High-throughput Experiments by Harvard on edX (Duration – 4 weeks)

This course covers various statistics topics such as multiple testing problems, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. You will then learn about statistical modelling and its application in high-throughput data.

Big Data, Genes, and Medicine by The State University of New York (Duration – 23 hours)

You will get to explore different topics on Big Data Science and Bioinformatics, including Big Data analytics on real datasets in a healthcare and biological context. It will also help you in preparing data, interpreting and visualizing the results, and sharing them.

Knowledge-Based AI: Cognitive Systems by Georgia Tech on Udacity (Duration – 7 Weeks)

This is a core course in artificial intelligence. It covers structured knowledge representations, problem-solving methodologies, planning, decision-making, and learning methods. Learn to design knowledge-based AI agents and human cognition, and build a relationship between knowledge-based artificial intelligence.

Artificial Intelligence for Robotics by Georgia Tech Masters on Udacity (Duration – 2 Months)

The course covers basic methods in Artificial Intelligence, including probabilistic inference, planning and search, localization, tracking, and control, with a focus on robotics. The program also covers programming examples and assignments for building self-driving cars.

Python for Data Science by the University of California, San Diego on edX (Duration – 4 Weeks)

In this advanced data science course, you will get to explore topics like Introduction to Spyder, Python for Data Science, Variables and Datatypes, Operators, Tuples, Dictionary, etc.

Big Data and Education by the University of Pennsylvania on edX (Duration – 8 Weeks)

The course will explore different methodologies for educational data mining, learning analytics, learning-at-scale, student modelling, and artificial intelligence communities. You will learn how and when to apply these methods.

Applied AI with DeepLearning by IBM on Coursera (Duration – 22 Hours)

The data science course will help you to understand different aspects of deep learning and models. It will also cover the usage of these modes by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines.
Hope this list helps you in making your decision to pick the most suitable course. All the best!



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