“I wanted to arm myself with basic knowledge so I can protect myself and patients.”
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The founding cohort opens October 2026. Enrol now to lock in your seat and 20% off. Understand the models behind modern clinical AI. No technical background required.
- Format
- Self-paced online
- Video lessons, notebooks, exercises
- Access starts
- October 2026
- Enrol now to lock in your seat
- Guarantee
- 3-day refund
- Full money-back, no questions
Founding cohort pricing — ends 8 September 2026
Course instructors
Completed core surgical training with a focus on plastic surgery, and now completing an MSc in Computing at Imperial College London. Teaches from the perspective of a clinician who's had to learn this from scratch, so nothing gets skipped or assumed.
Taught by Imperial College London-trained computer scientists. You'll be learning from people who are actively researching and building in the field.
TLDR
- → Applied machine learning for healthcare professionals
- → Founding cohort opens October 2026 — enrol now to lock in your seat
- → 20% off the standard price if you enrol before 8 September 2026
- → Build a working clinical predictor you can put on GitHub or reference at interview
- → Fully self-paced once it opens — learn at your own speed
- → Lifetime access to all lessons, notebooks and datasets
- → Certificate of completion issued when you finish
- → Taught by Imperial-trained computer scientists
- → 3-day money-back guarantee
20% off · Ends 8 September 2026
Access starts October 2026
Enrol now, pay once. Course opens October 2026. 3-day money-back guarantee.
Understand the models. Appraise the papers. Cut through the hype.
A hands-on machine learning course designed specifically for healthcare professionals. The founding cohort launches in October 2026 — enrol now to reserve your place at the introductory price. When it opens, you'll work through the material at your own pace and build a working clinical predictor from scratch: a portfolio-ready notebook you can put on GitHub, reference at interview, or use as a springboard for your own audit or research work.
You'll leave able to:
- •Understand the models behind modern clinical AI
- •Critically appraise ML papers and commercial tools
- •Build and evaluate models on clinical data yourself
Fully self-paced once it opens. Course material is released in October 2026. Enrol now to lock in your seat at the founding cohort price. Watch on any device. Rewatch as often as you need.
What we'll cover
Module 1: Python and data essentials for ML
A focused primer on the Python and Pandas you actually need to load, clean and explore clinical data. Skip it if you already code.
Module 2: Foundational mathematics for ML
The maths you actually need — vectors and matrices, probability and distributions, likelihood, and the intuition behind gradient descent. Taught for clinicians, no PhD required.
Module 3: Foundations of machine learning
Supervised vs unsupervised learning, train/test splits, and model evaluation. Train your first clinical predictor end-to-end.
Module 4: Working with clinical datasets
Handling missing data, class imbalance, feature engineering, and the practical realities of messy real-world clinical data.
Module 5: Interpreting and communicating model outputs
ROC curves, calibration, thresholds, and how to explain what your model is doing to a non-technical audience.
Module 6: Bias, fairness and safety
How ML models fail in clinical settings, where bias enters, and what to look for before you trust an output.
Module 7: Critical appraisal of clinical AI
A framework for reading AI papers and evaluating commercial tools with the same rigour you bring to a drug trial.
Module 8: Capstone: your clinical predictor
Ship a portfolio-ready notebook end-to-end. Something you can share, reference at interview, or extend into your own project.
This course
- ✓Taught by Imperial-trained computer scientists
- ✓Built around clinical use cases from lesson one
- ✓Fully self-paced with lifetime access
- ✓Includes a portfolio-ready capstone project
- ✓Certificate of completion
Typical alternatives
- ✗Generic examples with no clinical context
- ✗Hours of content with no clear endpoint
- ✗No hands-on project to point to afterwards
- ✗Access expires after a few months
- ✗No certificate or evidence of completion
Founding cohort price
20% off · Offer ends 8 September 2026
One-time payment. Course access opens October 2026. Lifetime access, certificate on completion.
⚠️ Please enter an actively-used email address at checkout. We'll email your login details when the course opens in October 2026.
Enrol now to secure this price. Access opens October 2026.
What you get
- ✓A working clinical predictor. A portfolio-ready notebook you can share on GitHub or reference at interview.
- ✓Lifetime access. Watch, rewatch and refer back to every lesson on any device, forever.
- ✓All course materials. Notebooks, code, datasets and exercises to download and keep.
- ✓Certificate of completion. Issued automatically once you finish the final module.
- ✓Access when the course opens. Login details emailed as soon as the founding cohort opens in October 2026.
- ✓3-day money-back guarantee. Try the course risk-free. Full refund within 3 days of purchase, no questions asked.
Refund policy
3-day money-back guarantee: If the course isn't what you were expecting, email us within 3 days of purchase for a full refund. No questions asked.
After 3 days: Refunds are considered on a case-by-case basis.