LangChain – Develop LLM-powered applications with LangChain

LangChain – Develop LLM-powered applications with LangChain

Course Objectives

• Learn the fundamentals of LangChain and its role in building LLM-powered applications
• Gain practical experience in integrating LLMs into various workflows
• Develop robust, scalable applications using LangChain with real-world datasets
• Implement advanced techniques like prompt engineering, chain-of-thought reasoning, and memory management for AI models
• Learn to deploy LLM-powered applications for various platforms, including web and mobile

Module 2: Building Basic Applications with LangChain

LangChain Basics:
Creating your first LangChain-based application
Integrating with OpenAI’s GPT API
Working with prompts and handling LLM responses

Module 3: Chains and Pipelines in LangChain

Understanding Chains:
What are Chains in LangChain?
Different types of chains: Simple chains, sequential chains, and parallel chains
Practical use of Chains to connect multiple LLM calls

Pipelines for Complex Workflows

Module 4: Prompt Engineering and Optimization

Module 5: Memory Management and Persistence

Module 6: Integrating External Tools and APIs

Module 7: Advanced Topics in LangChain

Module 8: Deploying and Scaling LLM-Powered Applications

Career Path After Completion

Upon completing this course, learners will be equipped to pursue careers in the following areas:

AI Application Developer:
Design and develop AI-driven applications using frameworks like LangChain.

Course Prerequisites

Familiarity with programming concepts (prior experience with Python is recommended)
Interest in learning AI-related technologies

Flexible Class Options

• Week End Classes For Professionals  SAT | SUN
• Corporate Group Trainings Available
• Online Classes – Live Virtual Class (L.V.C), Online Training