AI Governance Course Syllabus

Overview: This course provides a comprehensive introduction to AI governance, focusing on the ethical, regulatory, and risk management challenges in deploying AI systems responsibly. Designed for beginners, it combines conceptual learning with real-world case studies to build foundational knowledge in compliance, transparency, and governance frameworks. The course spans approximately 15-20 hours across six modules, featuring quizzes, peer-reviewed assignments, and guided project work to reinforce learning.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2-3 hours

• Introduction to key concepts in foundations of computing & algorithms
• Understanding algorithmic decision-making and its societal implications
• Case study analysis with real-world examples
• Assessment: Quiz and peer-reviewed assignment

Module 2: Neural Networks & Deep Learning

Estimated time: 1-2 hours

• Introduction to key concepts in neural networks & deep learning
• Understanding core AI concepts including neural networks and deep learning
• Case study analysis with real-world examples
• Assessment: Quiz and peer-reviewed assignment

Module 3: AI System Design & Architecture

Estimated time: 2 hours

• Introduction to key concepts in AI system design & architecture
• Discussion of best practices and industry standards
• Interactive lab: Building practical solutions
• Assessment: Quiz and peer-reviewed assignment

Module 4: Natural Language Processing

Estimated time: 3-4 hours

• Introduction to key concepts in natural language processing
• Understanding transformer architectures and attention mechanisms
• Implement prompt engineering techniques for large language models
• Discussion of best practices and industry standards
• Assessment: Quiz and peer-reviewed assignment

Module 5: Computer Vision & Pattern Recognition

Estimated time: 4 hours

• Introduction to computer vision and pattern recognition
• Exploring real-world applications and ethical concerns
• Guided project work with instructor feedback
• Assessment: Quiz and peer-reviewed assignment

Module 6: Deployment & Production Systems

Estimated time: 3 hours

• Introduction to deploying AI systems in production environments
• Hands-on exercises applying deployment & production systems techniques
• Guided project work with instructor feedback
• Assessment: Quiz and peer-reviewed assignment

Prerequisites

• Familiarity with basic computing concepts
• No prior technical experience in AI required
• Interest in ethics, policy, or organizational risk management

What You'll Be Able to Do After

• Understand core AI concepts including neural networks and deep learning
• Apply computational thinking to solve complex engineering problems
• Implement intelligent systems using modern frameworks and libraries
• Build and deploy AI-powered applications for real-world use cases
• Understand transformer architectures and attention mechanisms