LangChain: Develop AI Apps with Large Language Models Course Syllabus

Overview: This course provides a comprehensive introduction to building AI applications using LangChain and large language models. Designed for beginners with basic Python knowledge, it combines foundational AI concepts with hands-on development. The curriculum spans approximately 15-20 hours, structured across six modules that progress from computing fundamentals to real-world AI deployment. Learners will gain practical experience through labs, case studies, and a final project, preparing them to design and deploy intelligent systems using modern frameworks.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2 hours

• Understand transformer architectures and attention mechanisms
• Apply foundational computing principles to AI problems
• Practice algorithm design for efficient scaling
• Use computational thinking to solve engineering challenges

Module 2: Neural Networks & Deep Learning

Estimated time: 3 hours

• Introduction to neural networks and deep learning concepts
• Hands-on implementation of basic deep learning models
• Explore how deep learning powers large language models
• Apply techniques through interactive coding exercises

Module 3: AI System Design & Architecture

Estimated time: 4 hours

• Review AI system design patterns and best practices
• Analyze real-world case studies in AI architecture
• Learn scalable design for AI-powered applications
• Explore tools and frameworks used in industry

Module 4: Natural Language Processing

Estimated time: 3 hours

• Study core NLP concepts and applications
• Implement prompt engineering techniques
• Analyze real-world NLP use cases
• Use LangChain for language model integration

Module 5: Computer Vision & Pattern Recognition

Estimated time: 2 hours

• Introduction to computer vision fundamentals
• Explore pattern recognition in AI systems
• Case study analysis of vision-based applications

Module 6: Deployment & Production Systems

Estimated time: 4 hours

• Deploy AI models into production environments
• Build and test scalable AI pipelines
• Complete guided project with instructor feedback

Prerequisites

• Basic knowledge of Python programming
• Familiarity with fundamental AI and machine learning concepts
• Interest in generative AI and LLM application development

What You'll Be Able to Do After

• Design and implement AI-powered applications using LangChain
• Apply prompt engineering to optimize large language model outputs
• Build and deploy scalable AI systems for real-world use
• Utilize modern frameworks and libraries in AI development
• Create intelligent workflows integrating LLMs and external tools