Reinforcement learning (RL), is enabling exciting advancements in self-driving vehicles, natural language processing, automated supply chain management, financial investment software, and more. This program provides the theoretical framework and practical applications you need to solve big problems.
This course may be taken individually or as part of the Professional Certificate Program in Machine Learning & Artificial Intelligence. COMPLETING THE COURSE WILL CONTRIBUTE 3 DAYS TOWARDS THE CERTIFICATE.
This program includes the unique opportunity to present your organization’s specific technological challenges to MIT faculty via the Live RL Clinic, designed to help you identify if RL can help solve your problems, and what the right approach would be. The teaching team is comprised of recognized industry experts with experience working at 12 firms across multiple industries, from both startups and big tech. In this interactive “Clinic,” you will learn how to design reinforcement learning applications that address your specific issues.
- Understand the basic principles of RL and learn when RL can be applied to your business problem and how to pose the problem for obtaining maximum gains from RL
- Improve the performance of supervised learning systems by fine-tuning with RL methods
- Understand how to use popular Deep RL algorithms such as DQN and PPO
- Learn techniques for applying Deep RL methods to practical problems when it is impossible to collect large amounts of data
Who should attend
This program is ideally suited for technical professionals who wish to understand cutting-edge trends and advances in reinforcement learning. Professionals who are not sure of when and how to apply RL in engineering and business settings will find this program especially useful.
Prerequisites: To be able to take full advantage of this program, we recommend that participants have a mathematical background in linear algebra and probability, basic knowledge of deep-learning, and experience with programming (preferably Python).
This background will help participants follow some of the practical examples more effectively. There are two optional assignments in the program that will require a computer with Google CoLab that runs on any browser or Unix/Linux Terminal.
We welcome applications from professionals with significant experience and demonstrated career progression and success across levels, such as:
Representative job titles include:
- Research Scientist
- Machine Learning Engineer
- Software Engineer
- Data Scientist
- Data Analyst
- Business Analyst
- Product Manager
- Program Manager