![\"5](\"https:\/\/www.kdnuggets.com\/wp-content\/uploads\/c_5_free_university_courses_learn_data_science_1.jpg\")
Image generated with Segmind SSD-1B model<\/p>\n
Image generated with Segmind SSD-1B model<\/p>\n
Skilled data professionals are continuing to be in high demand. So it\u2019s a great time to break into data science. But how\u2014and where\u2014do you start? <\/p>\n
Should you sign up for bootcamps, professional certificates, and graduate programs to learn data science? Yes, these are all good options. However, you can learn data science for free and still switch careers successfully.<\/p>\n
To help you get started, we\u2019ve compiled a list of free and high-quality university courses that\u2019ll help you learn data science from the ground up. Because these courses have a structured curriculum, you don't have to worry about what to learn and in which order\u2014and only focus on learning and getting better.<\/p>\n
Let's get started!<\/p>\n
1. Introduction to Data Science with Python \u2013 Harvard <\/p>\n
If you need a refresher in Python programming before you start learning data science, check out CS50\u2019s Introduction to Programming with Python taught at Harvard University.<\/p>\n
After learning programming fundamentals with Python, you can check out this Introduction to Data Science with Python course, also from Harvard.<\/p>\n
In this course, you\u2019ll learn the following topics:<\/p>\n
Course link: Introduction to Data Science with Python<\/p>\n
2. Introduction to Computational Thinking and Data Science \u2013 MIT <\/p>\n
Introduction to Computational Thinking and Data Science from MIT is another good course to learn data science foundations. This course will help you gain familiarity with data science and essential statistics concepts.<\/p>\n
Here is an overview of what this course covers:<\/p>\n
Course link: Introduction to Computational Thinking and Data Science<\/p>\n
3. Statistical Learning \u2013 Stanford <\/p>\n
Statistical learning from Sanford University is yet another popular course to learn how the different machine learning algorithms work. <\/p>\n
The programming exercises in this course are in R. But you can also work through them using Python. I\u2019ll also suggest you to use the Python edition of the Introduction to Statistical Learning book (which is also free) as a companion to this course<\/p>\n
This course covers the following topics:<\/p>\n
Course link: Statistical Learning<\/p>\n
4. Topics in Mathematics of Data Science \u2013 MIT <\/p>\n
Even if you\u2019re familiar with building machine learning models using Python and Python libraries such as scikit-learn, you should understand certain math concepts as well.<\/p>\n
Learning math concepts will be helpful if you ever want to get into machine learning research and will also give you an edge in technical interviews. This is important learning these will help you get the edge will give you an edge in technical interview <\/p>\n
The Topics in Mathematics of Data Science course from MIT will teach you certain math topics related to data science. Specifically, advanced dimensionality reduction and clustering concepts.<\/p>\n
Here are some of the topics you\u2019ll learn:<\/p>\n
Course link: Topics in Mathematics of Data Science<\/p>\n
5. Data Science: Machine Learning \u2013 Harvard <\/p>\n
From one or more of the courses we\u2019ve seen thus far, you should be comfortable with:<\/p>\n
The Data Science: Machine Learning course from Harvard will help you review machine learning basics and apply them to build a recommender system.<\/p>\n
So this course teaches you:<\/p>\n
Course link: Data Science: Machine Learning<\/p>\n
Wrapping Up <\/p>\n
So you now have a list of high-quality data science courses from elite universities like Harvard, MIT, and Stanford to learn data science.<\/p>\n
From Python data science libraries to the inner workings of machine learning algorithms, you can check out one more of these courses to find the best fit for you. Happy learning!<\/p>\n