Artificial Intelligence Curriculum

Course Description:

This course provides an introduction to the field of Artificial Intelligence (AI). Students will learn the foundational concepts and techniques used in AI, including problem-solving, knowledge representation, machine learning, and natural language processing.

Lesson 1: Introduction to AI

• Overview of Artificial Intelligence
• History of AI
• Applications of AI

Lesson 2: Intelligent Agents

• Agents and environments
• Types of agents
• Agent architectures

Lesson 3: Problem Solving

• Problem-solving agents
• Search algorithms (e.g., breadth-first search, depth-first search)
• Heuristic search (e.g., A* algorithm)

Lesson 4: Knowledge Representation

• Knowledge representation schemes (e.g., propositional logic, predicate logic)
• Semantic networks
• Frames and scripts

Lesson 5: Machine Learning

• Introduction to machine learning
• Supervised learning
• Unsupervised learning
• Reinforcement learning

Lesson 6: Neural Networks

• Introduction to neural networks
• Perceptrons
• Multi-layer perceptrons (MLPs)
• Training neural networks

Lesson 7: Natural Language Processing

• Introduction to NLP
• Text processing
• Language modeling
• Machine translation

Lesson 8: Final Project

• Students work on a project applying AI techniques to a real-world problem

Assessment:

• Lessonly quizzes or assignments
• Final project demonstration and submission

Prerequisites:

Basic knowledge of programming and algorithms is recommended. No prior knowledge of AI is required.