AI Agents In Healthcare And Capstone Course Syllabus

Overview: This course provides an intermediate-level exploration of AI agents in healthcare, combining foundational knowledge with hands-on application through a capstone project. Learners will gain practical skills in designing and deploying AI systems tailored to real-world healthcare challenges. The curriculum spans approximately 17–22 hours, structured across six modules that progress from core computing principles to advanced AI deployment, culminating in a comprehensive capstone project. Ideal for professionals in AI or healthcare, the course emphasizes practical implementation using modern tools and frameworks.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2 hours

• Review of computing fundamentals and algorithmic thinking
• Application of foundational algorithms in healthcare contexts
• Exploration of commonly used tools and frameworks
• Interactive case study analysis with real-world healthcare examples

Module 2: Neural Networks & Deep Learning

Estimated time: 3 hours

• Review of neural network architectures and deep learning concepts
• Hands-on practice with deep learning frameworks
• Best practices in model training and optimization
• Interactive lab: Building a deep learning solution for healthcare data

Module 3: AI System Design & Architecture

Estimated time: 2 hours

• Introduction to AI system design principles
• Understanding scalable and modular architectures
• Industry standards and best practices in AI systems

Module 4: Natural Language Processing

Estimated time: 4 hours

• Foundations of NLP in clinical text processing
• Transformer architectures and attention mechanisms
• Prompt engineering techniques for large language models
• Tools and frameworks for healthcare NLP applications

Module 5: Computer Vision & Pattern Recognition

Estimated time: 3 hours

• Key concepts in medical image analysis
• Pattern recognition techniques in radiology and pathology
• Case studies on AI in diagnostic imaging

Module 6: Deployment & Production Systems

Estimated time: 4 hours

• Deploying AI models in clinical environments
• Building and testing production-ready healthcare applications
• Performance evaluation using healthcare-specific metrics
• Capstone project: Design and deploy an AI agent for a real-world healthcare scenario

Prerequisites

• Familiarity with basic AI or machine learning concepts
• Background in healthcare or clinical workflows (preferred)
• Programming experience with Python and common data science libraries

What You'll Be Able to Do After

• Implement intelligent AI systems using modern frameworks and libraries
• Apply prompt engineering techniques to large language models in healthcare
• Evaluate AI model performance with appropriate benchmarks
• Build and deploy AI-powered healthcare applications
• Design scalable algorithms for processing medical data