Artificial Intelligence in Health Care
offered by MIT University

Private University
168 acre campus
Estd. 1861

Artificial Intelligence in Health Care
at
MIT University
Overview

Develop a grounded understanding of how the use of AI is transforming health care

Duration	6 weeks
Total fee	₹2.10 Lakh
Mode of learning	Online
Course Level	UG Certificate

Artificial Intelligence in Health Care
at
MIT University
Highlights

Earn a certificate of completion from the MIT Sloan School of Management
Collaboration with GetSmarter to create a new class of learning experience
Interact with peers and learning facilitators through weekly class-wide forums
Guidance and one-on-one support from a University approved subject expert from GetSmarter
Pedagogy includes interactive content like video lectures, infographics, live polls, real-world case studies

Artificial Intelligence in Health Care
at
MIT University
Course details

Skills you will learn

Operations Data Processing

Who should do this course?

For professionals working for health care

What are the course deliverables?

Operations
Organizations & Leadership
Strategy & Innovation
Use of AI in diagnosis, patient monitoring and care
Build an AI decision framework
Hospital management and optimization through AI
Basics of machine learning, neural networks, and deep learning

More about this course

Course aims to equip health care leaders with a grounded understanding of the potential for AI innovations in the health care industry
Develop a holistic understanding of AI's growing role in health care through an immersive online experience that draws on realworld case studies
Candidates will gain an overview of the technology before delving into its practical adoption challenges, with regards to both hospital processes and resource management

Artificial Intelligence in Health Care
at
MIT University
Curriculum

AI and machine learning 'applications and foundations

Using AI for disease diagnosis and patient monitoring

Natural language processing and data analytics in health care

Interpretability in machine learning -benefits and challenges

Patient risk stratification and augmenting clinical workflows

Taking an integrated approach to hospital management and optimization

Artificial Intelligence in Health Care
at
MIT University
Faculty details

Dimitris Bertsimas

Dimitris Bertsimas is the Boeing Leaders for Global Operations Professor of Management, a Professor of Operations Research, and the Associate Dean for the Master of Business Analytics at MIT

Regina Barzilay

Regina Barzilay is a Delta Electronics professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory

Tommi Jaakkola

Tommi Jaakkola is the Thomas Siebel Professor of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society at MIT

Dina Katabi

Dina's research spans digital health, wireless sensors, mobile computing, machine learning and computer vision