Caroline Uhler
Caroline Uhler

Lead Instructor

Applied AI and Data Science Program
No Code and Agentic AI
Professional Certificate Program in Machine Learning & Artificial Intelligence

Caroline Uhler is an assistant professor in EECS and IDSS at MIT. She holds an MSc in Mathematics, a BSc in Biology, and an MEd in High School Mathematics Education from the University of Zurich. She obtained her PhD in Statistics from UC Berkeley in 2011. 

Her research focuses on mathematical statistics, in particular on graphical models and the use of optimization, algebraic and geometric methods in statistics, and on applications to biology. 

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Discover Applied AI and Data Science Program: a comprehensive curriculum designed for professionals seeking to excel in data analysis, agentic AI, visualization, and machine learning. Gain hands-on experience & earn a prestigious certificate of completion by MIT Professional Education.
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
Cathy Wu

Lead Instructor

Advanced Reinforcement Learning
Advanced Reinforcement Learning (Live Online)
Blended Professional Certificate: Technology Leadership Program
Professional Certificate Program in Machine Learning & Artificial Intelligence
Reinforcement Learning
Reinforcement Learning (Live Online)

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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