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LangChain
What you’ll learn
Our students work at..
Description
LangChain is an innovative platform that enables developers and AI practitioners to harness the power of powerful LLMs such as GPT-4 for creating dynamic applications, ranging from personal projects to enterprise-level solutions.
This course introduces LangChain to beginners in an approachable and easy-to-understand format. Each lecture includes demonstrations that walk you through setting up and using LangChain with an emphasis on simplicity. Practical coding exercises are included to help you practice constructing prompts, managing model interactions, and integrating external data sources directly within your browser—no separate setup is required. These exercises will validate your understanding and ensure you're on the right track when using LangChain effectively.
By the end of this course, you will not only understand the fundamentals of LangChain but also how to effectively implement it in various use cases, enabling you to bring your AI-driven applications to life.
What our students say
About the instructor
Janakiram MSV is an internationally recognized analyst, advisor and an architect in the field of Microservices, IoT, Edge Computing, and AI.
He was the founder and CTO of Get Cloud Ready Consulting, a niche Cloud Migration and Cloud Operations firm that was acquired by Aditi Technologies.
Through his speaking, writing, and analysis, he helps businesses take advantage of emerging technologies.
Janakiram is a regular contributor at Forbes and The New Stack. His articles are published at Business Insider, Computer Weekly, TechRepublic, and YourStory.
He is currently an advisor to Bay Area startups from the container storage, edge computing, and machine learning domains.
Janakiram is an adjunct faculty at the International Institute of Information Technology (IIIT-H) where he teaches Big Data, Cloud Computing, Containers, and DevOps to the students enrolled for the Master’s course.
Introduction
Building Blocks of LLM Apps
Overview of LangChain
Key Components of LangChain
Interacting with LLMs
Tips, Tricks, and Resources
Introduction to LCEL
Adding Memory to LLM Apps
Performing Retrieval
Implementing Chains
Using Tools
Building Agents
Conclusion
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