Machine Learning & MLOps Foundation
Programme Overview
Learn supervised and unsupervised learning, ML pipelines, model deployment and monitoring with health-data use cases.
Covers the complete machine learning lifecycle from model training through deployment and monitoring. Includes supervised and unsupervised learning, ML pipelines, model evaluation, versioning, and deployment basics — all applied to healthcare data use cases.
Curriculum Learning Areas
Detailed Curriculum Modules
4 Structured Phases • Hands-on Labs IncludedTarget Career Outcomes
Graduates of this track are actively qualified for the following industry positions:
Frequently Asked Questions
You should have foundational knowledge of Python and data analysis. If not, consider taking the Python for Data & Healthcare Automation programme first.
MLOps (Machine Learning Operations) covers the practices for deploying, monitoring and maintaining machine learning models in production environments.
Complementary Technology & Healthcare Programmes
Discover interconnected pathways in clinical analytics, AI, and medical coding aligned with your career goals.
Artificial Intelligence in Healthcare
- 4–6 Months • Advanced Track
- Computer Vision & Clinical NLP
- Medical imaging & diagnostic algorithms
Generative AI & LLM Applications for Healthcare
- 6–10 Weeks • Intensive
- Prompt Engineering, LLMs & RAG
- Automated EHR notes & triage agents
