A majority of the course will be dedicated to deep overviews into key topics in active research, including offline reinforcement learning, the theory of RL, multi-agent RL, Monte Carlo Tree Search, hierarchical RL, and model-based RL exploration.

Learn to navigate the ethical challenges inherent to AI development and implementation. Led by MIT experts Bernhardt Trout and Stefanie Jegelka, this course examines today’s most-pressing issues related to AI, ethics, and the ways that organizations can leverage the technology to benefit mankind.

Registration deadline: June 14, 2021

Discover how to build and utilize custom hardware for deep learning systems that extract meaningful information from your data.

Registration deadline: June 14, 2021

Master the data tools you need—from numerical linear algebra to convex programming—to make smarter decisions and drive enhanced results.

Registration deadline: June 7, 2021

Examine how the latest tools and algorithms driving modern and predictive analysis can be applied in different fields, even when using unstructured data.

Registration deadline: May 27, 2021

Explore neural networks and other critical algorithms, while enhancing your ability to formulate problems as machine learning tasks and identify the appropriate method of solution based on problem class.

Registration deadline: May 24, 2021