An active area of research, reinforcement learning has already achieved impressive results in solving complex games and a variety of real-world problems. However, organizations that attempt to leverage these strategies often encounter practical industry constraints. In this dynamic course, you will explore the cutting-edge of RL research, and enhance your ability to identify the correct approach for applying advanced frameworks to pressing industry challenges. 
Artificial intelligence (AI) is a powerful tool—but without the right system-wide architecture in place to support your initiatives, your organization is leaving value on the table. Featuring interactive exercises, industry speakers, and a hands-on group project, this dynamic five-day course is designed to equip you with the skills and strategies you need to deploy an AI systems engineering approach that maximizes the value of your digital products and services.

A tomada de decisão condiciona a evolução de qualquer empresa e seus responsáveis devem ser capazes de decidir da maneira segura, eliminando a casualidade do processo. O Machine Learning já é uma ferramenta fundamental para a tomada de decisões assertiva, possibilitando a análise de grandes quantidades de dados e eventos. Seu objetivo é reduzir espaços de incerteza e arbitrariedade por meio de aprendizado automático e análise eficiente de dados.

Reinforcement learning (RL), is enabling exciting advancements in self-driving vehicles, natural language processing, automated supply chain management, financial investment software, and more. In this three-day course, you will acquire the theoretical frameworks and practical tools you need to use RL to solve big problems for your organization.

Cathy Wu is the Gilbert W. Winslow Career Development Assistant Professor of civil and environmental engineering at MIT and has worked across many fields and organizations, including Microsoft Research, OpenAI, the Google X Self-Driving Car Team, AT&T, Caltrans, Facebook, and Dropbox. Wu is also the founder and Chair of the Interdisciplinary Research Initiative at the ACM Future of Computing Academy.

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Pulkit Agrawal is assistant professor of electrical engineering and computer science at MIT and leads the Improbable AI Lab, part of the Computer Science and Artificial Intelligence Lab at MIT and affiliated with the Laboratory for Information and Decision Systems. Agrawal also co-founded SafelyYou, an organization that builds fall prevention technology, and the AI Foundry, an incubator for AI startups.

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Seongkyu Yoon
Seongkyu Yoon

Dr. Seongkyu Yoon is a Professor in the Department of Chemical Engineering and the Ward Endowed Professor in Biomedical Sciences at UMass Lowell. He is also the UMass Site Director of the Advanced Mammalian Biomanufacturing Innovation Center and a contributor to the National Biomanufacturing Innovation Institute. Dr. Yoon runs a systems biology group that conducts research on systems biotechnology, life science informatics, bioprocess data analytics, and regulatory sciences with the objective of developing innovative biomanufacturing platforms for protein/cell/gene biotherapeutics.

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