AI Agents Architecture Python Course Syllabus

Overview: This course provides a comprehensive introduction to AI agent architecture using Python, designed for developers and tech enthusiasts looking to build intelligent systems. The curriculum spans approximately 15-18 hours across six modules, blending theoretical foundations with hands-on implementation. Learners will explore core AI concepts, neural networks, system design, natural language processing, computer vision, and deployment practices. Each module includes real-world case studies, practical exercises, and guided projects to reinforce learning. By the end, students complete a final project demonstrating proficiency in designing and deploying AI-powered applications.

Module 1: Foundations of Computing & Algorithms

Estimated time: 3 hours

• Review of tools and frameworks commonly used in AI development
• Introduction to computational thinking for problem solving
• Core programming concepts in Python for AI applications
• Case study analysis with real-world examples

Module 2: Neural Networks & Deep Learning

Estimated time: 4 hours

• Introduction to neural network architectures
• Deep learning fundamentals and model training
• Hands-on exercises applying neural networks and deep learning techniques
• Guided project work with instructor feedback

Module 3: AI System Design & Architecture

Estimated time: 2 hours

• Principles of AI agent architecture
• Best practices and industry standards in AI system design
• Interactive lab: Building practical AI solutions
• Case study analysis with real-world examples

Module 4: Natural Language Processing

Estimated time: 4 hours

• Introduction to key concepts in natural language processing
• Understanding transformer architectures and attention mechanisms
• Implementing prompt engineering techniques for large language models
• Review of NLP tools and frameworks

Module 5: Computer Vision & Pattern Recognition

Estimated time: 2 hours

• Introduction to computer vision fundamentals
• Pattern recognition techniques
• Hands-on exercises using computer vision libraries
• Case study analysis with real-world applications

Module 6: Deployment & Production Systems

Estimated time: 3 hours

• Introduction to deployment and production systems
• Review of tools and frameworks for deploying AI models
• Guided project work with instructor feedback
• Final project: Build and deploy an AI-powered application

Prerequisites

• Basic knowledge of Python programming
• Familiarity with fundamental programming concepts
• Interest in AI and intelligent systems development

What You'll Be Able to Do After

• Understand core AI concepts including neural networks and deep learning
• Implement prompt engineering techniques for large language models
• Build and deploy AI-powered applications for real-world use cases
• Apply computational thinking to solve complex engineering problems
• Design intelligent systems using modern AI frameworks and architectures