38 Free Courses on Coursera for Data Science
38 Free Courses on Coursera for Data ScienceThere are so many online resources for learning data science, and a great deal of it can be used at no cost. This collection of free courses hosted by Coursera will help you enhance your data science and machine learning skills, no matter your current level of expertise.
By Aqsa Zafar, Ph.D. Scholar in Machine Learning | Founder at MLTUT | Solopreneur | Blogger.
Coursera is an E-Learning platform and has a wide range of Free Data Science Courses. That’s why in this article, I am going to share with you Free Courses on Coursera for Data Science.
For these courses, You don’t need to pay a single buck. So take a few minutes to check out these Free Courses on Coursera for Data Science.
I divided these courses based on the knowledge level of Beginner, Intermediate, and Advanced. You can find the course according to your knowledge level.
Now without any further ado, let’s get started.
Free Courses on Coursera for Data Science
For your convenience, I created a table from where you can review the course according to Rating, Time to Complete, and Provider.
Beginner-Level
| S/N | Course Name | Rating | Time to Complete | Provider |
| 1. | Introduction to Statistics | 4.5/5 | 15 hours | Stanford University |
| 2. | Machine Learning | 4.9/5 | 61 hours | Stanford University |
| 3. | Foundations of Data Science: K-Means Clustering in Python | 4.6/5 | 29 hours | University of London |
| 4. | Data Analytics for Lean Six Sigma | 4.8/5 | 11 hours | University of Amsterdam |
| 5. | Computational Neuroscience | 4.6/5 | 26 hours | University of Washington |
| 6. | An Intuitive Introduction to Probability | 4.7/5 | 30 hours | University of Zurich |
| 7. | Probability and Statistics: To p or not to p? | 4.6/5 | 16 hours | University of London |
| 8. | Data Science Ethics | 4.8/5 | 15 hours | University of Michigan |
| 9. | Excel Basics for Data Visualizations | 4.1/5 | 1 hour | Coursera community |
| 10. | Predicting heart disease using Machine Learning | 4.1/5 | 50 minutes | Coursera community |
| 11. | Exploratory Time Series Analysis | 4.2/5 | 82 minutes | Coursera community |
| 12. | Practical Crowdsourcing for Efficient Machine Learning | 3.0/5 | 17 hours | Yandex |
| 13. | Population Health: Responsible Data Analysis | 4.6/5 | 21 hours | Leiden University |
Intermediate-Level
Advanced-Level
| S/N | Course Name | Rating | Time to Complete | Provider |
| 35. | Causal Inference | 3.3/5 | 12 hours | Columbia University |
| 36. | Causal Inference 2 | 3.4/5 | 6 hours | Columbia University |
| 37. | Data Science for Business with R Programming | 4.9/5 | 2 hours | Coursera community |
| 38. | Segment your market using factor analysis with R programming | NA | 2 hours | Coursera community |
Original. Reposted with permission.
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