Learn Data Science from Top Universities for Free
Where to find free lectures, seminars and complete courses from the likes of MIT, Stanford and Harvard.
By Rebecca Vickery, Data Scientist
I’m currently reading a book called ‘Ultralearning. Accelerate Your Career, Master Hard Skills and Outsmart the Competition’. This book talks about a learning technique that allows you to learn new skills and even completely new subjects in seemingly impossible time frames. According to the book, Ultralearning is “a strategy for acquiring skills and knowledge that is both self-directed and intense”.
The author of the book, Scott H Young, famously completed a personal challenge using ultralearning. The challenge that he set himself was to learn the entire 4-year MIT (Massachusetts Institute of Technology) curriculum for computer science in just 12 months. He successfully completed the challenge in 2012 and recorded a Ted Talk about his experiences called ‘Can you get an MIT education for $2,000?’.
Scott H Young was only able to complete his challenge for $2,000 because MIT makes most of their course material and lectures available for free via an online portal.
MIT is not the only university that does this. Many of the high ranking US universities make courses, lectures and other learning material available for free. Amongst this, is a wealth of material that is highly and often directly applicable to learning data science, machine learning and artificial intelligence.
Many of the high ranking US universities make courses, lectures and other learning material available for free.
I previously wrote an article called “How to Learn Data Science for Free” which provides an alternative, and free, learning path compared to more traditional university degree programs. However, if you are someone who learns better through a more traditional lecture-based course or would like to supplement this curriculum with deeper dive into related subjects the following free resources can help.
MIT is one of the leading institutes for both teaching and research in the field of modern computing. In 2001, the university launched its OpenCourseWare platform. The aim of which is to make lecture notes, problem sets, exams and video lectures, for the vast majority of its courses, available for free online.
There is a wealth of material here for data science-related subjects. Some of my personal favourites include:
- Introduction to Computational Thinking and Data Science.
- Mathematics of Machine Learning.
- Introduction to Computer Science and Programming in Python.
- Data, Models and Decisions.
Columbia, Applied Machine Learning
Andreas C. Muller, one of the core developers for the popular Python machine learning library Scikit-learn, is also a Research Scientist and lecturer at Columbia University.
Each year he publishes all material for his ‘Applied Machine Learning’ Course online. All the slides, lecture notes and homework assignments for the course are available in this Github repo.
The material in the repo is actually some of the best I’ve seen covering the area of actually applying machine learning in the real world. In addition to covering all aspects of the machine learning process from data exploration and cleaning to model evaluation and tuning, it also covers Github, unit testing and continuous integration. All extremely important aspects when you are applying machine learning in a real-world situation.
The Stanford School of Engineering regularly makes a selected number of its seminars available for free online. There are a select number of data science-related seminars available including ‘Human-Computer Interaction’, and ‘Robotics and Autonomous Systems’.You can find them via this link.
In addition, Stanford uploads many of its seminars and lectures to it’s Youtube channel — you can find that here. There are a wealth of videos covering data science, machine learning and deep learning on the channel.
Free Online Courses, Harvard
Harvard University publishes a selection of completely free online courses on its website. The courses are mostly hosted by edX so you also have the option of pursuing certification for each course for a small payment.
There are some really excellent courses here for learning data science. These include the following top picks, although there are many others:
- Principles, Statistical and Computational Tools for Reproducible Data Science.
- CS50: Introduction to Computer Science.
- Introduction to Linear Models and Matrix Algebra.
- CS50’s Introduction to Artificial Intelligence with Python.
The University of California, Berkeley also publish a range of courses on edX.org. There are some excellent data science-related courses including:
- Data Science: Machine Learning and Predictions.
- Data Science: Computational Thinking with Python.
- Data Science and Engineering with Spark.
There is such a wealth of free material available online for learning data science. This article covers some of the more traditional lecture-based approaches from high ranking universities. For more alternative resources I previously published my top 5 here.
Thanks for reading!
Bio: Rebecca Vickery is learning data science through self study. Data Scientist @ Holiday Extras. Co-Founder of alGo.
Original. Reposted with permission.
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