Techpratham can help you learn LangChain (Long Chain) so you can make smart AI apps that link LLMs to other tools, APIs, and sources of information. Learn how to make AI workflows that are aware of their surroundings, changeable, and ready for production.
Level
Advanced
Duration
8 weeks



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Techpratham's LangChain Training Program teaches students how to use the powerful framework to make LLM-powered apps. You will learn about LangChain's main parts, such as chains, memory, agents, and how to connect it to APIs, databases, and vector stores. The course focuses on making chatbots, RAG pipelines, and automating workflows. At the end, participants will know how to use LangChain to make AI solutions that can grow and work for businesses.
Working professional who is carrying more then 10 years of industry experience.
Access to updated presentation decks shared during live training sessions.
E-book provided by TechPratham. All rights reserved.
Module-wise assignments and MCQs provided for practice.
Daily Session would be recorded and shared to the candidate.
Live projects will be provided for hands-on practice.
Expert-guided resume building with industry-focused content support.
Comprehensive interview preparation with real-time scenario practice.
Introduction to LangChain
Learn the fundamentals and importance of LangChain in LLM applications.
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AI-Powered Customer Support Chatbot
Make a LangChain-based chatbot that remembers things and can carry on a conversation over multiple turns. It gets information from FAQs and a product database to give accurate and relevant answers, which lowers the cost of customer support.
Document Retrieval & Q/A Assistant
Use LangChain and vector stores like Pinecone to make a Q/A system. The assistant gets documents, summarizes them, and answers user questions with answers that are based on facts and take the user's situation into account.
Automated Workflow AI Agent
Create a LangChain agent that works with APIs for things like email, calendars, and Slack. As a smart digital assistant, the agent takes care of things like scheduling, sending reports, and answering business questions.

Why should I use LangChain instead of directly using LLM APIs?

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