From matrix calculus to Python to algorithms, build your foundational knowledge of machine learning with courses and resources from MIT Open Learning.
What is machine learning, and why does it matter? This powerful branch of AI enables systems to learn from data and get smarter over time, driving innovations in everything from healthcare to finance to gaming. Discover how machine learning works and build your foundational skills with seven free online courses and resources from MIT Open Learning.
Mathematics of Big Data and Machine Learning
Gain an understanding of the Dynamic Distributed Dimensional Data Model (D4M), a breakthrough in computer programming that combines graph theory, linear algebra, and databases to address problems associated with Big Data. Learn theories and apply a signal processing approach to practical problems.
Matrix Calculus for Machine Learning and Beyond
Master matrix calculus with techniques that allow you to think of a matrix holistically — an essential skill in machine learning and large-scale optimization. Learn to generalize and compute derivatives of important matrix factorizations as well as other operations, and understand how differentiation formulas must be reimagined in large-scale computing.
Understanding the World Through Data
Become a data explorer, learning how to leverage data and basic machine learning algorithms to understand the world.
Introduction to Machine Learning
Discover the principles, algorithms, and applications of machine learning from the point of view of modeling and prediction, including formulation of learning problems and concepts of representation, over-fitting, and generalization. Understand how these concepts are exercised in supervised learning and reinforcement learning, with applications to images and to temporal sequences.
Machine Learning with Python: From Linear Models to Deep Learning
Get an in-depth introduction to the field of machine learning — from linear models to deep learning and reinforcement learning — through hands-on Python projects. This course is part of the MITx MicroMasters Program in Statistics and Data Science.
Machine Vision
Understand the process of generating a symbolic description of the environment from an image, including the physics of image formation, image analysis, binary image processing, and filtering.
Visual Navigation for Autonomous Vehicles
Learn the mathematical foundations and state-of-the-art implementations of algorithms for vision-based navigation of autonomous vehicles. Get an overview of differential geometry and optimization, and gain knowledge of the fundamentals of two-view and multi-view geometric vision for real-time motion estimation, calibration, localization, and mapping.
