Agentic AI Content For Practitioners Teams Healthcare Course Syllabus

Overview: This intermediate-level course on Agentic AI for Practitioners, Teams, and Healthcare provides a comprehensive exploration of AI applications tailored to healthcare workflows. The curriculum spans foundational computing concepts to deployment of AI systems, emphasizing practical implementation in clinical and operational settings. With a total time commitment of approximately 15-18 hours, learners engage in hands-on exercises, case studies, and guided projects using modern AI frameworks. Designed for healthcare professionals and analysts, the course equips learners with skills to design and deploy intelligent systems that enhance patient care and automate healthcare processes.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2 hours

• Review of tools and frameworks commonly used in practice
• Introduction to key concepts in foundations of computing & algorithms
• Discussion of best practices and industry standards
• Hands-on exercises applying foundations of computing & algorithms techniques

Module 2: Neural Networks & Deep Learning

Estimated time: 4 hours

• Review of tools and frameworks commonly used in practice
• Interactive lab: Building practical solutions
• Guided project work with instructor feedback
• Discussion of best practices and industry standards

Module 3: AI System Design & Architecture

Estimated time: 3 hours

• Introduction to key concepts in AI system design & architecture
• Hands-on exercises applying AI system design & architecture techniques
• Guided project work with instructor feedback
• Assessment: Quiz and peer-reviewed assignment

Module 4: Natural Language Processing

Estimated time: 3 hours

• Review of tools and frameworks commonly used in practice
• Discussion of best practices and industry standards
• Case study analysis with real-world examples
• Hands-on exercises applying natural language processing techniques

Module 5: Computer Vision & Pattern Recognition

Estimated time: 4 hours

• Introduction to key concepts in computer vision & pattern recognition
• Interactive lab: Building practical solutions
• Guided project work with instructor feedback
• Review of tools and frameworks commonly used in practice

Module 6: Deployment & Production Systems

Estimated time: 2 hours

• Review of tools and frameworks commonly used in practice
• Guided project work with instructor feedback
• Case study analysis with real-world examples
• Discussion of best practices and industry standards

Prerequisites

• Basic understanding of AI concepts
• Familiarity with programming fundamentals
• Experience with data analysis or healthcare workflows preferred

What You'll Be Able to Do After

• Understand core AI concepts including neural networks and deep learning
• Implement intelligent systems using modern frameworks and libraries
• Apply computational thinking to solve complex engineering problems
• Build and deploy AI-powered applications for real-world healthcare use cases
• Evaluate model performance using appropriate metrics and benchmarks