15 free MIT data science courses
By Katherine Ouellette
Jumpstart your data science journey — one of the world’s fastest growing career paths! Build foundational skills and knowledge with these free online courses from MIT Open Learning.
Linear Algebra
Explore linear algebra and matrix theory through multidisciplinary topics.
Single Variable Calculus
Master the calculus of derivatives, integrals, coordinate systems, and infinite series.
Multivariable Calculus
Learn differential, integral, and vector calculus for functions with more than one variable.
Introduction to Probability and Statistics
Explore the foundations of probability and statistics — basic combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression.
Probability: The Science of Uncertainty and Data
Dive into probabilistic models, including random processes and the basic elements of statistical inference. (This course is part of the MITx MicroMasters Program in Statistics and Data Science.)
Fundamentals of Statistics
Develop a deep understanding of the principles of statistical inference — estimation, hypothesis testing, and prediction. (This course is part of the MITx MicroMasters Program in Statistics and Data Science.)
Understanding the World Through Data
Learn how to leverage basic data forms, tools, and machine learning algorithms to understand the world.
Introduction to Computer Science and Programming Using Python
Discover how Python 3.5 can be used as a tool to solve real-world analytical problems.
Introduction to Computational Thinking and Data Science
Learn how computation helps solve problems and gain confidence writing small programs to achieve practical goals.
Data Analysis: Statistical Modeling and Computation in Applications
Start using statistics and computation to analyze real data. (This course is part of the MITx MicroMasters Program in Statistics and Data Science.)
Introduction to Algorithms
Learn how to create mathematical models of computational problems and solve them using common algorithms, algorithmic paradigms, and data structures.
[Embed video: 2. Data Structures and Dynamic Arrays]
Introduction to Machine Learning
Discover the principles, algorithms, and applications of machine learning from the point of view of modeling and prediction.
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
Dive into deep learning and neural networks by applying linear algebra to probability, statistics, and optimization. Lecture 1: The Column Space of A Contains All Vectors Ax
Mathematics of Big Data and Machine Learning
Explore the Dynamic Distributed Dimensional Data Model, a breakthrough in computer programming that combines graph theory, linear algebra, and databases to address problems associated with big data.
Machine Learning with Python: from Linear Models to Deep Learning
Take a deep dive into linear models, deep learning, and reinforcement learning through hands-on Python projects.
These courses are available through MIT OpenCourseWare, MITx, and MITx MicroMasters Programs, which are part of MIT Open Learning. OpenCourseWare offers free, online, open educational resources from more than 2,500 courses that span the MIT undergraduate and graduate curriculum. MITx offers high-quality massive open online courses adapted from the MIT classroom for learners worldwide. MicroMasters Programs are graduate-level digital credentials from MIT that help learners accelerate their careers and Master’s degrees.
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