Enrolling Now AI & Medical Imaging In-person · Beirut

AIxMED, AI in Medical Imaging

A hands-on, in-person intensive bootcamp that takes you from machine-learning foundations to the architectures powering modern medical AI, with live coding on real medical imaging in Beirut.

10 sessions+ Capstone project
In-personIMCAN, Jnah, Beirut
Live codingReal medical imaging
12 seatsSmall, focused cohort
Enrol Now See Curriculum
An X-ray style scan of a human brain
Course overview

From ML foundations to modern medical AI

A comprehensive, hands-on program in artificial intelligence for medical imaging. Over ten live sessions you'll work through the full stack, from the machine learning cycle, SVMs and neural networks to CNNs, Transformers and medical image modalities, plus practical sessions with specialized tools and models, and finish with a capstone project of your own.

The Intensive Bootcamp

  • In-person at IMCAN, Centro Mall, Jnah, Beirut
  • September 21 – October 2, 2026, with ten daily sessions over two weeks
  • $150, capped at 12 participants
  • Basic Python proficiency required

Who it's for

  • Computer science and engineering students
  • Biomedical researchers and students
  • Software engineers moving into AI roles
  • Anyone who wants practical, code-first exposure to real medical imaging

What's included

  • 10 live sessions (1–2 hours each)
  • Hands-on coding exercises and real medical imaging examples
  • Session recordings, where available
  • Course completion certificate
  • Direct instructor access
The curriculum

Ten sessions, then a capstone

A hands-on progression from ML foundations to the architectures powering modern medical AI. Tap any module to expand.

1
ML FoundationsSessions 1–3 · The building blocks
  • Session 01 · Machine Learning Cycle: problem framing, data preparation, training, evaluation and iteration
  • Session 02 · Hands-on Scikit-Learn & SVM: support vector machines and classical ML on real datasets
  • Session 03 · Intro to Neural Networks: perceptrons, backpropagation, activations and training mechanics
2
Architectures & Medical ImagingSessions 4–6 · Models & modalities
  • Session 04 · CNNs & Transformers: convolutional networks and Vision Transformers for imaging
  • Session 05 · Medical Image Modalities: X-ray, MRI, CT, ultrasound and pathology, their challenges and preprocessing
  • Session 06 · Medical Tasks: classification, regression, segmentation and generation as core paradigms
3
Hands-on Medical AISessions 7–10 · Tools & models
  • Session 07 · Classification: BioMedCLIP, vision-language models on biomedical image-text pairs
  • Session 08 · Regression: RAD DINO, radiology regression for dose and outcome prediction
  • Session 09 · Segmentation: UNet, the gold-standard encoder-decoder architecture
  • Session 10 · Generation: Nvidia models for synthetic data and augmentation
4
Capstone ProjectApply the full pipeline
  • Apply the complete pipeline to a self-selected medical imaging problem
  • From data to model to evaluation, with instructor feedback
Your instructor

Learn from a working medical-AI researcher

Ahmad Mustapha, Doctoral Researcher at the American University of Beirut

Ahmad Mustapha

Doctoral Researcher · American University of Beirut

Ahmad specializes in AI for medical imaging, focusing on unsupervised deep learning, representation learning, and bias in medical AI systems. He has contributed to X-ray disease detection, vehicle detection, and multi-service AI platforms, with a mission to democratize access to medical AI.

Doctoral Researcher, AUB Medical AI Representation learning Bias in medical AI
Student stories

What the first cohort said

Real words from students who took the course.

★★★★★

"I truly learned a lot from this course and really appreciate the effort you put into this course."

H
HawraaFirst cohort
★★★★★

"I am grateful to have had the opportunity to be part of this first cohort through which I have learned a lot."

S
SundosFirst cohort
★★★★★

"We truly learned a lot throughout the sessions, and we really appreciate the time, guidance, and effort you put into making the series such a valuable experience for us."

A
AbeerFirst cohort
Enrol now

Reserve your seat in AIxMED

Enrolment is open, but the in-person Bootcamp is capped at just 12 seats. Tell us a little about yourself and we'll be in touch to confirm your place and share payment details.

  • In-person at IMCAN, Centro Mall, Jnah, Beirut
  • Sep 21 – Oct 2, 2026 · $150 · 12 seats
  • 10 live sessions + capstone, basic Python required
  • Completion certificate & direct instructor access

Enrolment request

We'll reply to confirm your seat, usually within 24 hours.

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