AI National Security Course Syllabus

Overview of the AI National Security Course on Coursera, designed by the Special Competitive Studies Project. This beginner-friendly program explores the strategic, policy, and operational impacts of artificial intelligence on national defense and global security. The course spans approximately 17–20 hours of content across six modules, combining conceptual learning with case studies, interactive labs, and guided projects. Ideal for non-technical learners, including policymakers, security analysts, and defense professionals interested in understanding how AI shapes modern security landscapes.

Module 1: Foundations of Computing & Algorithms

Estimated time: 3 hours

• Case study analysis with real-world examples
• Review of tools and frameworks commonly used in practice
• Interactive lab: Building practical solutions
• Assessment: Quiz and peer-reviewed assignment

Module 2: Neural Networks & Deep Learning

Estimated time: 1.5 hours

• Introduction to key concepts in neural networks & deep learning
• Hands-on exercises applying neural networks & deep learning techniques
• Discussion of best practices and industry standards
• Guided project work with instructor feedback

Module 3: AI System Design & Architecture

Estimated time: 4 hours

• Hands-on exercises applying AI system design & architecture techniques
• Interactive lab: Building practical solutions
• Review of tools and frameworks commonly used in practice
• Guided project work with instructor feedback

Module 4: Natural Language Processing

Estimated time: 2.5 hours

• Case study analysis with real-world examples
• Discussion of best practices and industry standards
• Interactive lab: Building practical solutions

Module 5: Computer Vision & Pattern Recognition

Estimated time: 2 hours

• Interactive lab: Building practical solutions
• Case study analysis with real-world examples
• Review of tools and frameworks commonly used in practice

Module 6: Deployment & Production Systems

Estimated time: 3.5 hours

• Case study analysis with real-world examples
• Interactive lab: Building practical solutions
• Review of tools and frameworks commonly used in practice
• Discussion of best practices and industry standards

Prerequisites

• Familiarity with basic computing concepts
• Interest in national security or public policy
• No prior technical experience in AI required

What You'll Be Able to Do After

• Understand core AI concepts including neural networks and deep learning
• Evaluate model performance using appropriate metrics and benchmarks
• Implement intelligent systems using modern frameworks and libraries
• Apply AI to national security contexts such as threat analysis and surveillance
• Understand the strategic and policy implications of AI in defense and intelligence