WEEK 1:

• lectures:
  • Outline of the course
  • What is data science and machine learning - and why healthcare
  • How does a machine learning model learn?
• practical: Setting up jupyter notebook (practical exercise)

WEEK 2:

• lecture: Introduction to Python Programming
• practicals:
  • Introduction to Python Programming (1, 2, 3, 4, 5)
  • Coding a Medical Calculator

WEEK 3:

• lectures:
  • A Generalisable Data Science Pipeline: How to Apply Data Science to Real World Problems
  • Key Challenges and Considerations for Real-World use of ML in Healthcare
• practicals:
  • Diagnosing breast cancer with AI
  • Stroke prediction (with an imbalanced dataset)

WEEK 4:

• lectures:
  • An Introduction to Neural Networks
  • Deep Learning: Computer Vision
• practical: CXR classification using open dataset

WEEK 5:

• lecture: Deep Learning: Sequential data and NLP
• practical: Extracting Insights from Medical Research Papers with NLP

WEEK 6:

• lecture: Commercial Applications in Healthcare
• practical: Classifying breast cancer molecular subtypes using gene expression data