Overview
What you will study
In the Advanced Reinforcement Learning course offered by Massachusetts Institute of Technology (MIT) , you’ll receive an advanced overview of the cutting-edge RL topics that are driving exciting advancements in machine learning. Through interactive lectures and exercises, you’ll acquire a multi-faceted glimpse into the development and potential of RL, from the perspectives of statistics, optimal control, economics, operational research, and other disciplines.
You will additionally have the opportunity to put your learning into practice during hands-on clinics, in which you will use advanced algorithms to solve real-world problems, and then discuss your solutions with the class and instructors during office hours. You will leave the course armed with a broad understanding of reinforcement learning as a tool, mathematical framework, and active field of study.
Programme Structure
The program focuses on:
- RL, from the perspectives of statistics, optimal control, economics, operational research, and other disciplines
- Determine the reinforcement learning framework (e.g. goal-directed, hierarchical, offline reinforcement learning, bandits) that is best-suited to solve a specific problem
- Select the most promising algorithms for an already-formulated reinforcement learning problem
- Recognize the limitations of reinforcement learning
- Judge whether a situation is suited for these strategies
Key information
Duration
- Full-time
- 2 days
- Part-time
- 2 days
Start dates & application deadlines
- Starting
- Apply before
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Language
Credits
Delivered
Disciplines
Artificial Intelligence Machine Learning View 152 other Short Courses in Artificial Intelligence in United StatesWhat students do after studying Computer Science & IT
This information is based on LinkedIn alumni data for graduates from 2018 to 2024 and may not fully represent all career outcomes
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.
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Other requirements
General requirements
- This course is designed for mid-career professionals who are actively involved in or want to learn more about reinforcement learning.
- Participants should be familiar with the basics of RL, including exact dynamic programming algorithms, Q-learning, deep neural networks, machine learning libraries (e.g. PyTorch or Tensorflow), and basic deep RL methods (DQN, policy gradient methods).
Tuition Fee
-
International
2500 USD/fullTuition FeeBased on the tuition of 2500 USD for the full programme during 2 days. -
National
2500 USD/fullTuition FeeBased on the tuition of 2500 USD for the full programme during 2 days.
Living costs for Boston
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.