📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Federated Learning for Multi-Center Medical Image Diagnostics, from foundations to a certified capstone project.
Outline
Prepare multi‑modal MRI datasets using MONAI transforms • Configure isolated federated client nodes in Google Colab • Apply data partitioning strategies for realistic multi‑center simulation
Outline
Build a 3D U‑Net for volumetric tumor segmentation with MONAI • Implement Federated Averaging (FedAvg) using the Flower framework • Orchestrate multi‑client training without sharing raw MRI data
Outline
Benchmark federated vs. centralized models using Dice, IoU, precision, recall • Generate 3D tumor volume visualizations for research abstracts • Prepare figures and performance tables for high‑impact journal submission
Earn government-registered certification in Federated Learning for Multi-Center Medical Image Diagnostics
e-Certificate and e-Marksheet issued on successful completion.
