Artificial Intelligence in Health Care

MIT Sloan School of Management

Artificial Intelligence

About Programme

Why attend Artificial Intelligence in Health Care?

In Artificial Intelligence in Health Care, the MIT Sloan School of Management and the MIT J-Clinic aim to equip health care leaders with a grounded understanding of the potential for AI innovations in the health care industry. The course explores types of AI technology, its applications, limitations, and industry opportunities.

The potential of artificial intelligence (AI) to transform health care — through the work of both organizational leaders and medical professionals — is increasingly evident as more real-world clinical applications emerge.

As patient data sets become larger, manual analysis is becoming less feasible. AI has the power to efficiently process data far beyond our own capacity, and has already enabled innovation in areas including chemotherapy regimens, patient care, breast cancer risk, and even ICU death prediction.

With this program, the MIT Sloan School of Management and the MIT J-Clinic aims to equip health care leaders with a grounded understanding of the potential for AI innovations in the health care industry. The Artificial Intelligence in Health Care online short course explores types of AI technology, its applications, limitations, and industry opportunities. Techniques like natural language processing, data analytics, and machine learning will be investigated across contexts such as disease diagnosis and hospital management.

Programme Content

Self-Paced Online

Orientation Module

Welcome to your Online Campus

Module 1

AI and Machine Learning - Applications and Foundations

Module 2

Using AI for Disease Diagnosis and Patient Mentoring

Module 3

Natural Language Processing and Data Analytics in Health Care

Module 4

Interpretability in Machine Learning - Benefits and Challenges

Module 5

Patient Risk Stratification and Augmenting Clinical Workflows

Module 6

Taking an Integrated to Hospital Management and Optimization

Programme Audience

This course aims to empower leaders in both business and medical roles with the knowledge to understand the transformative role of artificial intelligence (AI) in health care. Key learning areas include the basics of machine learning, neural networks, and deep learning. Participants can expect to immediately and directly apply the knowledge gained in this course in their own roles within the health care sector. Professionals working for health care providers will learn to identify the types of problems that AI techniques can help solve.

Programme Benefits

Self-Paced

This course is delivered in our Self-Paced Online format which enables you to participate at your own pace within weekly modules. This course runs over 6 weeks with an estimated 6-8 hours per week of study time

Certificate

Earn a certificate of course completion from the MIT Sloan School of Management

Interactive

You will learn through a variety of formats including interactive videos, practice quizzes, presentations, assignments, and discussion forums

Support

You will have access to a Success Adviser who will help you manage your time, and support you with any administrative or technical queries you might have

Testimonials

"One will be astonished, including myself, by the lineup of speakerslecturers who are global leadersinnovators, great thinkers who have made complex AI data analytics simple, initially a challenge, and pragmatic. Assignment questions generated by students were expected to think beyond the basics of AI data, surpass basic knowledge, and explore the weaknesses and deficits of AI, and come up with an innovative solution to problems and curiosities that may remain unsolved. As practicing physicians, we can see how AI enhances patient care, could mitigate burnout, and, in the future, create an AI hybrid. A truly innovative and analytic course; I commend it!"

Arthur J

"The course was thorough and covered what I expected for my understanding of AI. I was able to work out how my case scenario would be assisted by AI, the expected benefits and challenges"

Sridharan J

"Engaging in this course has provided both insight and aptitude to intelligently navigate the AI integration into healthcare."

Rebecca R

"Thanks for supporting to finish this course."

Meihui H

"Excellent Program"

Carlo U

"Excellent course and I highly recommend healthcare professionals to pursue it"

Samyukta S

"I was disappointed to find out that I have paid over 2K for a course of recorded videos. No access to live interactive classes with a lecturer to be able to ask questions. Contents were useful but when you pay that much money you expect to sit in a virtual class with a lecturer. Quite overpriced for what it is !"

Hamid Z

"Understanding AI in the context of health care is completely different to other fields and the necessary requirements that differ to other industries. This course provides key insights into the aims of utilising AI in medicine, the various considerations, implementation and understanding of the ethical aspects and governance required."

Kripa S

"Overall, this course provides a solid introduction to the role of artificial intelligence in health care, particularly for learners who are looking to understand foundational concepts rather than technical implementation. It succeeds in clearly explaining the core ideas behind AI, machine learning, and optimization, and it offers valuable perspective on the key requirements for deploying AI responsibly within clinical environments. Through real-world examplesranging from diagnostic imaging to hospital operationsthe course helps learners appreciate both the potential and the limitations of AI in health care today. One of the courses strengths is the way it highlights practical considerations such as interpretability, trust, bias, data readiness, and workflow integration. These themes recur across modules and help build an understanding of what it truly takes for an AI tool to be viable in a clinical setting. In that sense, the course is effective at setting expectations for leaders, clinicians, and administrators who need to assess AI solutions rather than build them. That said, learners seeking a hands-on, technical curriculum will likely find the course lacking. It does not cover the practical aspects of developing AI models, working with datasets, or implementing machine learning tools. Topics such as coding, model training, evaluation metrics, or system architecture are discussed conceptually rather than in a way that allows for practical application. The course is therefore best suited for individuals who want strategic or managerial understanding, not those wanting to build AI systems themselves. Finally, the forum component of the course did not add meaningful value. While intended to encourage discussion and peer exchange, it felt disconnected from the core learning experience and did not significantly contribute to understanding or engagement. Enhancements in moderation, more guided prompts, or integration with assignments could make this feature more impactful in future iterations. In short, this course is a good fit if your goal is to gain a conceptual and high-level view of AI in health care. It is less appropriate if you are seeking technical depth, hands-on practice, or applied machine learning training."

Xavier S

"Excellent course"

Prashanth A

Testimonial Source