Core curriculum
The whole course at a glance
Three modules of short lessons, then an assessment. Each lesson introduces and explains key concepts as needed, allowing learners to progress independently without prior AI experience.
- 3 modules
- 14 core lessons
- 15-20 min per lesson
- One depth for everyone
The core lessons
Each takes 15 to 20 minutes and has a few ungraded checks and one hands-on piece. Finish with the post-course quiz.
Module 1Fundamentals of AI
Module 2Radiology Basics
Module 3 · coming soonAI in Clinical Practice
The path
Work through the stops in order. Pick any stop to jump to it.
Modules and lessons
Lessons marked Coming soon show their planned outline for now.
- 1.1
AI Around You
Available - 1.2
How Models Learn
Available - 1.3
Data & Labels
Available - 1.4
Measuring Performance
Available - 1.5
Limits & Failures
Available
Module 2
Radiology Basics: Images, Systems & Reports
What is radiology, and how does a scan become data?
Module overview →- 2.1
What Radiology Is
Available - 2.2
The Journey of a Scan
Available - 2.3
Images as Data
Available - 2.4
Reading a Radiology Report
Available
- 3.1
AI in Radiology & Medicine
Coming soon - 3.2
Does It Work, and Is It Worth It?
Coming soon - 3.3
Thinking With AI
Coming soon - 3.4
Responsibility & Patients
Coming soon - 3.5
The Future of AI in Radiology
Coming soon
Finish
Assessment
Closes the core curriculum.
- A
Assessment
Coming soonA short graded quiz. It is the only graded step in the course.
Optional tracks
Open these at any time. They are not required to finish the core course.
Research Lab
Six hands-on data science labs in Google Colab, each built around a clinical question.
- Lab 1 · Python, Colab and GitHub
- Lab 2 · Clinical data
- Lab 3 · Evaluating an AI tool
- Lab 4 · Imaging AI
- Lab 5 · Reports and LLMs
- Lab 6 · Your projectOptional