20 Best AI In Healthcare Courses To Take In 2024
These AI in healthcare courses are a great way to learn from experts who stay up-to-date with the field. Here's a summary of each course to help you understand who it’s for and what makes it valuable.
Best AI In Healthcare Courses Shortlist
Here's my shortlist of the best AI in healthcare courses that I think are helpful:
- AI in Healthcare Specialization (Stanford University)
- Artificial Intelligence in Health Care (MIT Management Executive Education)
- AI for Health Care: Concepts and Applications (Harvard University)
- Machine Learning for Healthcare (MIT Professional Education)
- AI in Family Medicine: Transforming Your Practice (AAFP)
- AI-Based Medicine Technical Expertise CME (University of Florida)
- Artificial Intelligence in Pharma and Biotech (MIT Management Executive Education)
- Implementing Health Care AI into Clinical Practice (Harvard University)
- Generative AI for Healthcare (Google Cloud)
- Data Science for AI in Healthcare (Johns Hopkins University)
- How to Use ChatGPT in Healthcare (edX)
- AI in Healthcare. Hype or Help? (KU Leuven)
- Artificial Intelligence in Nursing (Elite Learning)
- AI and Digital Transformation in Healthcare (University of Cambridge)
- AI in Medicine Certificate (University of Illinois Urbana-Champaign)
- AI in Healthcare (Johns Hopkins University)
- Artificial Intelligence in Healthcare (Queen's University)
- Foundations of AI in Healthcare (University of Melbourne)
- Artificial Intelligence in Health Care Certificate Program (Michener)
- AI-Powered Chest Disease Detection and Classification (Coursera)
Find more details about each course below.
Overview Of The Best AI In Healthcare Courses
1. AI in Healthcare Specialization (Stanford University)
This course helps healthcare providers understand how AI technologies and machine learning address specific challenges in the healthcare industry, including patient care safety, quality, and medical research. It explores the integration of AI with medical science, practice, and business while introducing foundational AI concepts to drive innovation.
- Who It’s For: Healthcare providers and computer science professionals seeking to enhance collaboration between their fields.
- Topics Covered:
- Introduction to Healthcare
- Clinical data basics
- Machine learning fundamentals for healthcare
- Evaluating AI in healthcare
- AI in Healthcare capstone
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 1 month
- How Many Hours Of Instruction: 10 hours per week
- Eligibility Requirements: None
- Price: Free
- Take The Course: Coursera
2. Artificial Intelligence in Healthcare (MIT Management Executive Education)
This course provides an understanding of AI adoption in healthcare, focusing on practical challenges related to hospital processes and resource management. It covers the use of AI for diagnosis, patient care, and hospital optimization while teaching how to assess its viability for specific healthcare settings.
- Who It’s For: Business and medical leaders who want to understand and apply AI to solve problems within the healthcare sector.
- Topics Covered:
- AI and machine learning foundations
- AI for disease diagnosis and patient monitoring
- Natural language processing in healthcare
- Interpretability in machine learning
- Patient risk stratification
- Integrated hospital management and optimization
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 6 weeks
- How Many Hours Of Instruction:6-8 hours a week
- Eligibility Requirements: None
- Price: $2,950
- Take The Course: MIT Management Executive Education
3. AI for Health Care: Concepts and Applications (Harvard University)
This AI course covers ethical and safety principles for applying AI in healthcare, including data analysis, using large language models, and their real-world applications. It also guides participants through implementing AI healthcare projects, addressing challenges, and exploring future advancements while ensuring compliance and stakeholder engagement.
- Who It’s For: Senior managers and executives responsible for developing and implementing AI strategies in their organizations.
- Topics Covered:
- Introduction to AI
- Implementing AI in healthcare organizations
- Algorithmic bias and data ethics
- Safety and regulation
- Evaluating and scaling AI in healthcare
- AI and intrapreneurship
- Online, In-Person, or Both? Both
- Exam Required? No
- Duration: 4 days
- How Many Hours Of Instruction: 5 hours per day
- Eligibility Requirements: None
- Price: $2,600
- Take The Course: Harvard University
4. Machine Learning for Healthcare (MIT Professional Education)
This course provides strategies for using machine learning and AI to tackle key healthcare challenges, including connecting disparate health data, predicting outcomes, and personalizing care. In practical lab exercises, participants will work with real-world health data to apply machine learning and causal inference techniques.
- Who It’s For: Professionals with a background in coding and an interest in healthcare technology
- Topics Covered:
- Clinical data and risk assessment
- Risk stratification lab
- Clinical NLP lab
- ML for treatment selection
- Causal inference lab
- Disease progression prediction
- Payer analytics
- Survival modeling lab
- Medical imaging lab
- Dataset shift detection
- Nias and fairness in AI
- Privacy and synthetic data
- Online, In-Person, or Both? In-Person
- Exam Required? No
- Duration: 3 days
- How Many Hours Of Instruction: 9 hours a day
- Eligibility Requirements: None
- Price: $2,300
- Take The Course: MIT Professional Education
5. AI in Family Medicine: Transforming Your Practice (AAFP)
This 3-part course is designed to teach you how to use the emerging technology of artificial intelligence (AI) to support and enhance your practice. It shows how to use AI and machine learning to enhance family medicine by reducing administrative tasks and improving patient outcome predictions, covering current and emerging AI solutions and helping participants evaluate and integrate these technologies.
- Who It’s For Family medicine practitioners interested in digital transformation
- Topics Covered:
- AI Introduction
- Applied in Primary Care
- AI—Solutions
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: Self-paced
- How Many Hours Of Instruction: Varies
- Eligibility Requirements: None
- Take The Course: AAFP
6. AI-Based Medicine Technical Expertise CME (University of Florida)
This course teaches Python programming for AI in medicine, including its setup and use with Jupyter. It covers Python’s history and provides foundational lessons to start programming for medical research applications.
- Who It’s For: Healthcare professionals aiming to enhance their technical knowledge of AI
- Topics Covered:
- Python programming basics
- History of Python
- Setting up Python environment
- Using Jupyter for coding
- Programming for medical research
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 8 hours
- How Many Hours Of Instruction: Self-paced
- Eligibility Requirements: None
- Price: $200
- Take The Course: University of Florida
7. Artificial Intelligence in Pharma and Biotech (MIT Management Executive Education)
This course explores the applications of AI and ML in the pharmaceutical and biotech industry, focusing on early drug discovery, disease research, and patient stratification. It also covers how AI can aid in biomarker identification, disease tracking, and the design and management of clinical trials.
- Who It’s For: Business leaders, researchers, data scientists, and analysts in pharma and biotech who want to understand and apply AI tools in their work.
- Topics Covered:
- AI in the pharmaceutical industry
- Early drug discovery
- Disease modeling
- Biomarkers and patient stratification
- Clinical trial design and management
- Business and innovation in pharma
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 6 weeks
- How Many Hours Of Instruction: 6-8 hours per week
- Eligibility Requirements: None
- Price: $2,950
- Take The Course: MIT Management Executive Education
8. Implementing Health Care AI into Clinical Practice (Harvard University)
This course teaches how to design and implement AI-enhanced clinical workflows, assess model performance, and manage model deployment and maintenance. It covers building and guiding multidisciplinary teams through AI project stages, including workflow analysis, data modeling, and change management.
- Who It’s For: Healthcare professionals looking to implement AI
- Topics Covered:
- Health Care AI and Decision Science
- Workflow Mapping
- Accuracy Metrics
- Model Selection
- ML-Ops and Architecture Design
- Heart Rhythm AI Case Study
- Model Maintenance
- Study Design and Change Management
- Change Management Planning
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 4 days
- How Many Hours Of Instruction: 6 hours per day
- Eligibility Requirements: None
- Price: $2,600
- Take The Course: Harvard University
9. Generative AI for Healthcare (Google Cloud)
This course introduces generative AI and large language models, explaining their concepts and how they can be applied in healthcare. It covers tools like Vertex AI and explores prompt engineering to develop effective question-and-answer prompts for medical use cases.
- Who It’s For: Healthcare professionals and tech specialists interested in applying generative AI and large language models in healthcare settings.
- Topics Covered:
- Introduction to Generative AI for Healthcare
- LLMs in Healthcare
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 3 weeks
- How Many Hours Of Instruction: 1 hour per week
- Eligibility Requirements: None
- Price: Free
- Take The Course: Coursera
10. Data Science for AI in Healthcare (Johns Hopkins University)
This course provides training on applying machine learning and artificial intelligence to solve healthcare problems, emphasizing methods for analyzing and validating data-driven algorithms in clinical settings. It fosters interdisciplinary skills needed to bridge the gap between healthcare professionals and technical experts.
- Who It’s For: Clinicians and engineers interested in learning about machine learning and artificial intelligence applications in healthcare.
- Topics Covered:
- Terminologies
- Data science fundamentals
- Research study anatomy
- Case study
- Machine Limitations
- Interpretable AI in Healthcare
- Society and AI in Healthcare
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: Semester-long
- How Many Hours Of Instruction: Varies
- Eligibility Requirements: None
- Take The Course: Johns Hopkins University
11. How to Use ChatGPT in Healthcare (edX)
This course demonstrates how to leverage ChatGPT to enhance patient care, improving medical data access, and optimize healthcare administration. It covers practical applications and addresses ethical and legal considerations related to using AI in healthcare.
- Who It’s For: Healthcare providers and administrators
- Topics Covered:
- Introduction to Using ChatGPT in Healthcare
- Building with ChatGPT in Healthcare
- Advanced ChatGPT Techniques in Healthcare
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 1 week
- How Many Hours Of Instruction: 1-2 hours per week
- Eligibility Requirements: Prior knowledge of ChatGPT and healthcare is required
- Price:
- Free
- With certificate ($20)
- Take The Course: edX
12. AI in Healthcare. Hype or Help? (KU Leuven)
This course explores AI in healthcare from both the healthcare professional's and developer’s perspectives, focusing on evaluating AI's benefits, limitations, and risks. It also covers the technical background of establishing and validating AI algorithms within the healthcare context.
- Who It’s For: Healthcare professionals and scholars looking to understand AI principles, its value in healthcare, and related ethical and regulatory guidelines.
- Topics Covered:
- Impact of AI on Healthcare
- AI Principles and Concepts
- Evaluating Benefits and Limitations of AI
- AI's Value and Applications in Healthcare
- Data Requirements and Ethical Guidelines
- Regulatory Boundaries in AI
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 10 weeks
- How Many Hours Of Instruction: 2-5 hours per week
- Eligibility Requirements:
- High school mathematics
- Interest in healthcare
- Price:
- Free
- With certificate ($80.60)
- Take The Course: edX
13. Artificial Intelligence in Nursing (Elite Learning)
This course explains the role of artificial intelligence and machine learning in healthcare, with a focus on nursing. It highlights how these technologies are used in clinical settings and emphasizes the importance of understanding their ethical implications.
- Who It’s For: Nurses and nursing administrators
- Topics Covered:
- Descriptions of Artificial Intelligence and Augmented Reality
- Importance of AI and Machine Learning for Nurses
- Impact of AI on Healthcare
- Ethical Considerations in AI and Machine Learning
- Clinical Scenarios of AI in Nursing
- Online, In-Person, or Both? Online
- Exam Required? No
- Eligibility Requirements: None
- Price:
- Elite learning membership ($44/year)
- Take The Course: Elite Learning
14. AI and Digital Transformation in Healthcare (University of Cambridge)
This course introduces fundamental concepts of artificial intelligence and digital transformation in healthcare, covering global healthcare systems, data requirements, and AI model evaluation. It explores real-world applications, ethics, governance, and the integration of digital tools like EHRs and telemedicine to build a roadmap for AI development in clinical practice.
- Who It’s For: Healthcare professionals, researchers, and developers interested in understanding AI concepts, digital transformation, and their application within the healthcare sector.
- Topics Covered:
- Introduction to AI and Digital Transformation
- Digital Transformation in Healthcare
- Governance and Ethics in AI
- AI-Driven Healthcare
- Crafting an AI Roadmap for the Future
- Online, In-Person, or Both? In-Person
- Exam Required? No
- Duration: 1 week
- How Many Hours Of Instruction: 8 hours per day
- Eligibility Requirements: None
- Take The Course: University of Cambridge
15. AI in Medicine Certificate (University of Illinois Urbana-Champaign)
This course teaches how to read and understand AI literature in medicine, assess data-driven decisions, and identify AI tools and techniques. It focuses on preparing participants to participate in selecting and implementing AI-based medical software.
- Who It’s For: Medical professionals with foundational knowledge of artificial intelligence collaborate with computer science experts, engage with vendors, and enhance healthcare delivery and patient care.
- Topics Covered:
- Data and Decisions
- Concepts of Machine Learning
- Deep Learning
- Advanced Deep Learning
- Deploying AI in Practice
- Real-World AI Applications in Medicine
- Online, In-Person, or Both? Online
- Exam Required? Yes
- Duration: 6 months
- How Many Hours Of Instruction: Varies
- Eligibility Requirements: None
- Price: $750
- Take The Course: University of Illinois Urbana-Champaign
16. AI in Healthcare (Johns Hopkins University)
This course teaches practical skills for implementing AI in healthcare, including evaluating AI rigorously, designing trials, and understanding generative AI for decision-making. It focuses on overcoming challenges, responsible AI use, and creating tailored action plans for organizational integration.
- Who It’s For: Healthcare professionals, educators, researchers, and policymakers interested in using artificial intelligence to improve patient outcomes
- Topics Covered:
- AI applications in diagnosis and treatment
- Risk management
- Ethical considerations
- Technology integration
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 1 day
- How Many Hours Of Instruction: 7 hours and 30 minutes
- Eligibility Requirements: None
- Price: $1,250
- Take The Course: Johns Hopkins University
17. Artificial Intelligence in Healthcare (Queen's University)
This course breaks down fundamental AI concepts, practical applications, and machine learning models in healthcare. It focuses on training principles, ethical considerations, and strategies for evaluating and integrating AI systems into medical practice.
- Who It’s For: Healthcare professionals and administrators
- Topics Covered:
- Introduction to AI in Healthcare
- Basics of Machine Learning
- Principles of Machine Learning
- Decision Trees and Deep Networks
- Convolutional Networks and Transformers
- Ethics of AI in Healthcare
- Applications of AI Ethics
- Online, In-Person, or Both? Online
- Exam Required? No
- Eligibility Requirements: None
- Price: $745
- Take The Course: Queen's University
18. Foundations of AI in Healthcare (University of Melbourne)
This course gives healthcare professionals practical knowledge to understand and implement AI and machine learning in medical settings. It covers strategic deployment, ethical decision-making, and designing AI solutions to improve patient care and outcomes.
- Who It’s For: Healthcare professionals, MedTech professionals, healthcare data analysts, medical AI researchers, clinical informatics specialists, bioinformatics scientists, and those pursuing careers in product development, regulations, and quality management.
- Topics Covered:
- Basics Of AI In Healthcare
- Machine Learning Concepts
- Deep Learning And Neural Networks
- AI Regulations And Data Privacy
- Ethical AI Use In Healthcare
- Strategic AI Implementation
- Designing AI Solutions For Healthcare
- Online, In-Person, or Both? Online
- Exam Required? No
- Duration: 6 weeks
- How Many Hours Of Instruction: 7 hours per week
- Eligibility Requirements:
- Bachelor's degree
- Skills equivalent to Level 7 of the Australian Qualifications Framework (AQF 7) through relevant professional experience
- Price: $1,490
- Take The Course: University of Melbourne
19. Artificial Intelligence in Health Care Certificate Program (Michener)
This course teaches how to leverage AI to assist healthcare providers by compiling and presenting crucial information for decision-making. It focuses on using AI for disease management, patient prioritization, diagnosis support, and generating preliminary reports.
- Who It’s For: Healthcare professionals and technologists
- Topics Covered:
- AI Fundamentals
- AI and Data Science
- AI Development in Healthcare
- Managing AI Implementations
- AI Project
- Online, In-Person, or Both? Online
- Exam Required? Yes
- Duration: 15 months
- How Many Hours Of Instruction: Varies
- Eligibility Requirements:
- Completed application form
- Detailed resume
- Proof of credentials (official transcripts)
- Proof of English language assessment (if English is a second language)
- Non-refundable application fee ($75 for domestic, $110 for international)
- Price:
- Total tuition fees for Domestic students ($6,756)
- Total tuition fees for International students ($8, 784)
- Take The Course: Michener
20. AI-Powered Chest Disease Detection and Classification (Coursera)
This course teaches how to build an AI-powered system for detecting and classifying chest diseases from X-ray images. It focuses on automating disease detection to reduce costs and time in medical diagnosis and provides hands-on experience that can be applied directly to healthcare projects and portfolios.
- Who It’s For: Medical imaging professionals and data scientists
- Topics Covered:
- AI-Powered chest disease detection
- Disease classification using X-Ray images
- Automation to reduce detection cost and time
- Practical applications In Healthcare
- Online, In-Person, or Both? Online
- Exam Required? Yes
- Duration: 2 hours and 8 minutes
- How Many Hours Of Instruction: Self-paced
- Eligibility Requirements: None
- Price: Free
- Take The Course: Class Central
Join For More Insights
To stay updated on the latest trends, best practices, and solutions related to your medical practice, subscribe to The Medical Practice newsletter.