Course duration
6 weeks
Excluding orientation
Language
English
Access resources from start date
Effort
6–8 hours per week
Self-paced learning online
Course overview
The combined percentage of surveyed health care organizations that are in some way focused on increasing their proportion of AI-assisted applications.
Accenture (Jan, 2019).
The projected value of the AI health care market by 2021.
Business News Daily (Jun, 2019).
Duration: 6 weeks (excluding orientation)
The medical industry constantly strives to improve patient care, and better prediction is crucial in achieving this goal. Machine learning (ML) and artificial intelligence (AI) have proven to be effective tools for enhancing diagnosis, personalizing treatments, and understanding disease progression.
The Artificial Intelligence in Health Care online short course offered by the MIT Sloan School of Management and the MIT J-Clinic is a great option for those interested in exploring the potential impact of AI in healthcare. The course provides a comprehensive overview of AI's applications and limitations in the healthcare industry, examines the challenges it can help address, and highlights successful AI deployments through industry case studies.
Regina Barzilay, world-renowned for her work in AI and breast cancer detection, leads the course, providing valuable insights and knowledge from MIT, a leading institution for developing ML methods with health care applications.
Is this course for you?
Regardless of whether you work in finance or engineering, this program can provide you with an understanding of how artificial intelligence and machine learning can revolutionize the healthcare industry. By taking this course, you'll gain a deeper appreciation for the issues that AI technology and techniques can address in health care. The artificial intelligence in healthcare course covers critical topics such as the fundamentals of ML, neural networks, and deep learning, making it easy to apply what you learn directly to health care roles.
Machine Learning
ML is an AI field that employs algorithms to learn from data and generate predictions. This program introduces you to ML algorithms and their application in the healthcare industry.
Neural Networks
The MIT Sloan Artificial Intelligence in Health Care online course delves into various neural network types and their applications in health care data. Neural networks, a ML algorithm, are particularly effective at tasks like image recognition and classification.
Deep Learning
Moreover, the MIT AI in healthcare course provides a primer on deep learning. Deep learning is the practice of using artificial neural networks with many layers to identify complex data patterns. It is a machine learning subfield focusing on algorithms learning from unstructured or unlabeled data. Through this program, you'll learn about deep learning techniques and how they are employed in health care.
Computer Science Experts
The course is taught by experts in computer science from MIT and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). CSAIL is one of the world's leading AI research centers. The program's faculty members are at the forefront of their field and are developing state-of-the-art technology that is already being used in various industries.
Course overview
Introduction
Duration: 6 weeks (excluding orientation)
The medical industry constantly strives to improve patient care, and better prediction is crucial in achieving this goal. Machine learning (ML) and artificial intelligence (AI) have proven to be effective tools for enhancing diagnosis, personalizing treatments, and understanding disease progression.
The Artificial Intelligence in Health Care online short course offered by the MIT Sloan School of Management and the MIT J-Clinic is a great option for those interested in exploring the potential impact of AI in healthcare. The course provides a comprehensive overview of AI's applications and limitations in the healthcare industry, examines the challenges it can help address, and highlights successful AI deployments through industry case studies.
Regina Barzilay, world-renowned for her work in AI and breast cancer detection, leads the course, providing valuable insights and knowledge from MIT, a leading institution for developing ML methods with health care applications.
Is this course for you?
Regardless of whether you work in finance or engineering, this program can provide you with an understanding of how artificial intelligence and machine learning can revolutionize the healthcare industry. By taking this course, you'll gain a deeper appreciation for the issues that AI technology and techniques can address in health care. The artificial intelligence in healthcare course covers critical topics such as the fundamentals of ML, neural networks, and deep learning, making it easy to apply what you learn directly to health care roles.
Machine Learning
ML is an AI field that employs algorithms to learn from data and generate predictions. This program introduces you to ML algorithms and their application in the healthcare industry.
Neural Networks
The MIT Sloan Artificial Intelligence in Health Care online course delves into various neural network types and their applications in health care data. Neural networks, a ML algorithm, are particularly effective at tasks like image recognition and classification.
Deep Learning
Moreover, the MIT AI in healthcare course provides a primer on deep learning. Deep learning is the practice of using artificial neural networks with many layers to identify complex data patterns. It is a machine learning subfield focusing on algorithms learning from unstructured or unlabeled data. Through this program, you'll learn about deep learning techniques and how they are employed in health care.
Computer Science Experts
The course is taught by experts in computer science from MIT and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). CSAIL is one of the world's leading AI research centers. The program's faculty members are at the forefront of their field and are developing state-of-the-art technology that is already being used in various industries.
What will set you apart
Course curriculum
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 monitoring
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 approach to hospital management and optimization
Get more information
Faculty Director
Regina Barzilay
School of Engineering Distinguished Professor for AI and Health, MIT Center for Machine Learning in Health; AI Faculty Lead, Jameel Clinic
Earn a certificate of completion from MIT Sloan
Explore the potential of AI and ML in health care, and earn an official digital certificate of completion from MIT Sloan School of Management.
This program also counts toward an MIT Sloan Executive Certificate, which you can earn by completing four programs; three from your chosen certificate track and one completed in person. Find out more.
Get more information
Want to know more?
Why choose GetSmarter?
GetSmarter operates as edX's partner for premium online short course products from the world's leading universities and institutions. With edX, we leverage our people, technology, and resources to power your education and your potential.
We deliver market-led courses that equip working professionals with the expertise required to upskill, reskill or kickstart a completely new career. Through a data-driven approach, we analyze future skills requirements and ensure all courses address this need. We ensure that leading universities and institutions are your expert guides and our people, technology, and resources are your engine – together we power more than just education, we power your potential.
Read more about GetSmarter here and edX here.
Find out more about GetSmarter’s approach to digital learning, course design, and online delivery here.
Payment options
You can pay your course fees before the course starts, or you may opt for a split payment plan on courses that are nine weeks and shorter. For courses 10 weeks and longer, there is a three-part payment plan available. To find out more about payment options please visit our Payment and Financing page, or contact an Enrollment Adviser, to find out which option you qualify for.
Manage your time
GetSmarter's learning model is designed to help you, as a working professional, improve your skills without compromising on work and family responsibilities. The course work is broken up into weekly, manageable bite-sized modules, with incremental deadlines, designed to help you pace yourself over the duration of the course and allow you the legroom to work when it suits you best.
At the beginning of each module you'll be presented with the course content and assignments necessary for completion. You also have access to your Success Adviser who will help you manage your time, and support you with any administrative or technical queries you might have.
Seek employer assistance
By improving your skills and industry knowledge, you'll have an influence on the success of your organization. Why wouldn't you ask your boss to help you fund your studies if it's going to have an impact on the way you do business?
Of our past students, 37 percent have received financial assistance from their employers. You can ask for help, too. Here is a guide to show you how to request financial assistance from your employer.
If you are a Learning & Development (L&D) manager, or involved in training and upskilling for an organization, you can request information regarding our corporate offering on our GetSmarter for business page.
How to change your start date
As part of our commitment to your professional development, GetSmarter offers you a two-week period to change your course start date or request your money back if you’re not fully satisfied.
To qualify for a deferral of your course start date, or to cancel your enrollment and receive a refund of your course fee, your request would need to reach our Success Advisers before the release of Module 2. For more information, please read our Terms and Conditions.
Discover the Online Campus
The Online Campus will be your virtual classroom for the duration of your course. Through its easy-to-use interface you'll have access to a diverse variety of course content formats including: interactive videos, module notes, practice quizzes, presentations, assignment briefs, and additional web resources.
On the Online Campus, you'll also be able to ask questions and interact with your fellow students and teaching team through the discussion forums. If you are looking for your Online Campus login, please visit your Account page here.
Leading organisations invest in this course for their employees.
Learn more about edX For Business
Want to buy this course for your team? Chat with us to get started.
Get Started