AI for Medical Professionals

AI for Medical Professionals

Instructor: AI CERTs Team

Access provided by EY

8 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

8 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Apply AI in Clinical Workflows: Use AI tools to support diagnostics, improve triage accuracy, and streamline clinical documentation workflows.
Use Predictive Analytics for Better Outcomes: Identify high-risk patients, predict complications, and support earlier interventions with AI insights.
Automate Healthcare Processes: Reduce clinician workload with AI assisted documentation, chart reviews, and workflow optimization.
Strengthen Safety and Quality with AI: Use AI insights to reduce errors, improve care consistency, and enhance patient safety.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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

Learn more about Coursera for Business

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

There are 8 modules in this course

Healthcare is rapidly evolving as artificial intelligence transforms diagnostics, workflows, and patient care. The AI for Medical Professionals Certification stands out as a beginner-friendly, hands-on course, uniquely designed to bridge the gap between clinical practice and AI adoption—empowering clinicians and healthcare professionals to confidently apply AI tools in real-world settings, without coding or technical expertise.

You’ll learn how AI can reduce documentation time, improve triage efficiency, support faster clinical decision-making, strengthen diagnostics, and optimize healthcare operations. Through practical exercises and real-world case studies, the course explores how AI-powered systems, predictive analytics, and intelligent automation are reshaping modern healthcare delivery. By the end of the course, you’ll be equipped to use AI responsibly to improve patient outcomes, streamline clinical processes, and strengthen data-driven healthcare practices. Enroll in the AI for Medical Professionals Certification Online to build future-ready clinical skills and lead smarter, more efficient healthcare delivery.

This module introduces the overall certification structure and explains how the learning experience is organized throughout the course. To support different learning preferences, the content is offered in multiple formats, including Videos, eBooks, Audiobooks, and Podcasts. Each format covers the same key concepts, giving you the flexibility to learn in the way that works best for you. You can choose any format based on your preferred learning style and move through the course at your own pace.

What's included

12 videos1 reading1 assignment2 plugins

12 videosTotal 141 minutes

Navigation Video2 minutes
Course Introduction5 minutes
Audiobook Introduction6 minutes
Audiobook 1 -What is AI for Doctors43 minutes
Podcast 1 - What is AI for Doctors39 minutes
1.1 From Decision Support to Diagnostic Intelligence4 minutes
1.2 What Makes AI in Medicine Unique?5 minutes
1.3 Types of Machine Learning in Medicine8 minutes
1.4 Common Algorithms and What They Do in Healthcare8 minutes
1.5 Real-World Use Cases Across Medical Specialties9 minutes
1.6 Debunking Myths About AI in Healthcare5 minutes
1.7 Real Tools in Use by Clinicians Today6 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 130 minutes

2 pluginsTotal 30 minutes

Module 1: What is AI for Doctors? 15 minutes
ACTIVITY: Multiple Choice15 minutes

What's included

8 videos1 reading1 assignment2 plugins

8 videosTotal 157 minutes

Audiobook 2 -AI in Diagnostics & Imaging77 minutes
Podcast 2 - AI in Diagnostics & Imaging45 minutes
2.1 Introduction to Neural Networks: Unlocking the Power of AI9 minutes
2.2 Convolutional Neural Networks (CNNs) for Visual Data: Seeing with AI's Eyes6 minutes
2.3 Image Modalities in Medical AI: AI's Multi-Modal Vision5 minutes
2.4 Model Training Workflow: From Data Labeling to Deployment – The AI Lifecycle in Medicine5 minutes
2.5 Human-AI Collaboration in Diagnosis: The Power of Augmented Intelligence4 minutes
2.6 FDA-Approved AI Tools in Diagnostic Imaging: Trust and Validation6 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 230 minutes

2 pluginsTotal 30 minutes

Module 2: AI in Diagnostics & Imaging 15 minutes
ACTIVITY: Accordion15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 177 minutes

Audiobook 3 -Introduction to Fundamental Data Analysis85 minutes
Podcast 3 - Introduction to Fundamental Data Analysis52 minutes
3.1 Understanding Clinical Data Types—EHRs, Vitals, Lab Results8 minutes
3.2 Structured vs. Unstructured Data in Medicine8 minutes
3.3 Role of Dashboards and Visualization in Clinical Decisions8 minutes
3.4 Pattern Recognition and Signal Detection in Patient Data10 minutes
3.5 Identifying At-Risk Patients via Trends and AI Scores6 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 330 minutes

2 pluginsTotal 30 minutes

Module 3: Introduction to Fundamental Data Analysis15 minutes
ACTIVITY: Multiple Select15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 220 minutes

Audiobook 4 -Predictive Analytics & Clinical Decision Support – Empowering Proactive Patient Care129 minutes
Podcast 4 - Predictive Analytics & Clinical Decision Support – Empowering Proactive Patient Care60 minutes
4.1 Predictive Models for Risk Stratification – Sepsis and Hospital Readmissions5 minutes
4.2 Logistic Regression, Decision Trees, Ensemble Models6 minutes
4.3 Real-Time Alerts – Early Warning Systems (MEWS, NEWS)6 minutes
4.4 Sensitivity vs. Specificity – Metric Choice by Clinical Need7 minutes
4.5 ICU and ER Use Cases for AI-Triggered Interventions7 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 430 minutes

2 pluginsTotal 30 minutes

Module 4: Predictive Analytics & Clinical Decision Support – Empowering Proactive Patient Care15 minutes
ACTIVITY: Problem Statement15 minutes

What's included

9 videos1 reading1 assignment2 plugins

9 videosTotal 197 minutes

Audiobook 5 -NLP and Generative AI in Clinical Use93 minutes
Podcast 5 - NLP and Generative AI in Clinical Use66 minutes
5.1 Foundations of NLP in Healthcare5 minutes
5.2 Large Language Models (LLMs) in Medicine8 minutes
5.3 Prompt Engineering in Clinical Contexts7 minutes
5.4 Generative AI Use Cases – Summarization, Counselling Scripts, Translation6 minutes
5.5 Ambient Intelligence: Next-Gen Clinical Documentation3 minutes
5.6 Limitations & Risks of NLP and Generative AI in Medicine5 minutes
5.7 Case Study3 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 530 minutes

2 pluginsTotal 30 minutes

Module 5: NLP and Generative AI in Clinical Use15 minutes
ACTIVITY: Tab15 minutes

What's included

8 videos1 reading1 assignment2 plugins

8 videosTotal 153 minutes

Audiobook 6 -Ethical and Equitable AI Use69 minutes
Podcast 6 - Ethical and Equitable AI Use49 minutes
6.1 Algorithmic Bias – Race, Gender, Socioeconomic Impact7 minutes
6.2 Explainability and Transparency (SHAP and LIME)9 minutes
6.3 Validating AI Across Populations7 minutes
6.4 Regulatory Standards – HIPAA, GDPR, FDA/EMA Compliance4 minutes
6.5 Drafting Ethical AI Use Policies5 minutes
6.6 Case Study: Biased Pulse Oximetry Detection3 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 630 minutes

2 pluginsTotal 30 minutes

Module 6: Ethical and Equitable AI Use15 minutes
ACTIVITY: True or False15 minutes

What's included

9 videos1 reading1 assignment2 plugins

9 videosTotal 140 minutes

Audiobook 7 -Evaluating AI Tools in Practice69 minutes
Podcast 7 - Evaluating AI Tools in Practice36 minutes
7.1 Core Metrics: Understanding the Basics5 minutes
7.2 Confusion Matrix & ROC Curve Interpretation4 minutes
7.3 Metric Matching by Clinical Context5 minutes
7.4 Interpreting AI Outputs: Enhancing Clinical Decision-Making4 minutes
7.5 Critical Evaluation of Vendor Claims: Ensuring Reliability and Effectiveness6 minutes
7.6 Red Flags in Commercial AI Tools: Recognizing and Mitigating Risks6 minutes
7.7 Checklist: “10 Questions to Ask Before Buying AI Tools”6 minutes