Stanford University
AI in Healthcare Specialization
Stanford University

AI in Healthcare Specialization

Matthew Lungren
Serena Yeung
Mildred Cho

Instructors: Matthew Lungren

Get in-depth knowledge of a subject
4.7

(2,303 reviews)

Beginner level
No prior experience required
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.7

(2,303 reviews)

Beginner level
No prior experience required
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Identify problems healthcare providers face that machine learning can solve

  • Analyze how AI affects patient care safety, quality, and research

  • Relate AI to the science, practice, and business of medicine

  • Apply the building blocks of AI to help you innovate and understand emerging technologies

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English
90 practice exercises

See how employees at top companies are mastering in-demand skills

 logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Stanford University

Specialization - 5 course series

Introduction to Healthcare

Introduction to Healthcare

Course 111 hours

What you'll learn

  • The major challenges of the U.S.healthcare system

  • Issues you may encounter in efforts to improve healthcare delivery and the healthcare system

  • Who the key stakeholders are in the U.S. healthcare system

Skills you'll gain

Health Policy, Medicaid, Health Care, Medicare, Health Care Administration, Health Care Procedure and Regulation, Managed Care, Healthcare Industry Knowledge, Healthcare Ethics, Hospital Experience, Health Systems, Value-Based Care, Pharmaceuticals, and Medical Billing

What you'll learn

  • How to apply a framework for medical data mining

  • Ethical use of data in healthcare decisions

  • How to make use of data that may be inaccurate in systematic ways

  • What makes a good research question and how to construct a data mining workflow answer it

Skills you'll gain

Clinical Data Management, Data Mining, Feature Engineering, Electronic Medical Record, Health Informatics, Health Care, Clinical Research, Unstructured Data, Text Mining, Data Collection, Data Processing, Data Transformation, Medical Imaging, and Data Ethics

What you'll learn

  • Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.

  • Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.

  • Learn important approaches for leveraging data to train, validate, and test machine learning models.

  • Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.

Skills you'll gain

Machine Learning Algorithms, Machine Learning, Deep Learning, Supervised Learning, Artificial Neural Networks, Health Informatics, Healthcare Ethics, Healthcare Industry Knowledge, Responsible AI, Applied Machine Learning, Data Processing, Reinforcement Learning, Medical Science and Research, Data Ethics, Health Policy, Artificial Intelligence and Machine Learning (AI/ML), and Health Care

What you'll learn

  • Principles and practical considerations for integrating AI into clinical workflows

  • Best practices of AI applications to promote fair and equitable healthcare solutions

  • Challenges of regulation of AI applications and which components of a model can be regulated

  • What standard evaluation metrics do and do not provide

Skills you'll gain

Responsible AI, Regulatory Compliance, Health Technology, Decision Support Systems, Clinical Assessment, Healthcare Industry Knowledge, Clinical Informatics, Continuous Monitoring, Data Ethics, Health Informatics, Health Equity, AI Personalization, Predictive Modeling, Clinical Research Ethics, and Application Deployment
AI in Healthcare Capstone

AI in Healthcare Capstone

Course 510 hours

What you'll learn

Skills you'll gain

Applied Machine Learning, Machine Learning, Artificial Intelligence, Performance Tuning, Risk Modeling, Data Validation, Responsible AI, Data Ethics, Healthcare Industry Knowledge, Application Deployment, Health Informatics, Patient-centered Care, Analysis, Clinical Data Management, Data Collection, Health Care Procedure and Regulation, Healthcare Ethics, and Feature Engineering

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Matthew Lungren
Stanford University
2 Courses41,810 learners
Serena Yeung
Stanford University
2 Courses41,810 learners

Offered by

Compare with similar products

Rating
Level
Skills
Last updated
Number of practice exercises
Degree eligibility
Part of Coursera Plus

You might also like

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Coursera Plus

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions