Langchain for beginners : Build GenAI LLM Apps in Easy Steps (Udemy.com)
A Step-by-Step Guide to Master LangChain:RAG, Agents, MCP, Ollama, LangSmith & Streamlit with OpenAI & OpenSource Models
Created by: Bharath Thippireddy
Last updated September 2026
What you will learn
- Learn what LangChain is how it simplifies using LLMs in our applications
- Use OpenAI LLMS in a python application
- Use Open Source LLMS like Mistral,Gemma in a python application
- Run Open Source LLMs on your local machine using OLLAMA
- Use PromptTemplates to reuse and build dynamic prompts
- Understand how to use the LangChain expression language
- Create Simple and Regular Sequential chains using LCEL
- Work with multiple LLMs in a single chain
- Learn why and how to maintain Chat History
- Learn what embeddings are and use the Embeddings Model to find text Similarity
- Understand what a Vector Store is and use it to store and retrieve Embeddings
- Understand the process of Retrieval Augmented Generation(RAG)
- Implement (RAG) to use our own data with LLMs in simple steps
- Analyze images using Multi Modal Models
- Understand what Agents are and implement agents
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.6 out of 5higher than 67% of them
- Reviews1,267#345 of 1,183 by number of reviews
- Length4.8 hoursshorter than 54% of them
- Last updatedSeptember 2026more recently than 91% of them
Course Description
LangChain has quickly become one of the most important frameworks for building real-world applications using large language models (LLMs). This course is designed to help you get started with LangChain and progressively master its powerful features, all through clear and simple examples.
Whether you’re a Python developer, an AI enthusiast, or someone curious about LLMs, this course will give you the tools and confidence to build intelligent applications using both OpenAI and open-source models.
What You’ll Learn
• What LangChain is and how it simplifies integrating LLMs into applications
• Use OpenAI LLMs in Python to generate and process natural language
• Use open-source LLMs like Mistral and Gemma in your own apps
• Run open-source models locally on your machine using Ollama
• Build dynamic prompts using PromptTemplates
• Understand and apply the LangChain Expression Language (LCEL)
• Create simple and regular sequential chains to control workflow logic
• Use multiple LLMs within a single chain for flexible responses
• Maintain and use chat history to create context-aware apps
• Learn about embeddings and apply them to measure text similarity
• Understand vector stores and use them to store and search embeddings
• Learn the Retrieval-Augmented Generation (RAG) workflow
• Implement RAG with your own data using LangChain in simple steps
• Analyze images using multi-modal models
• Understand what Agents are and implement agents
• Use Model Context Protocol (MCP) in your agents to access external tools
• Trace and implement observability your LLM applications using LangSmith
• Build real-world LLM-powered apps using Streamlit and LangChain
Who This Course Is For
• Python developers exploring AI and LLM integration
• Anyone looking to build chatbots, assistants, or smart tools using LLMs
• Professionals working on NLP, search, RAG, or agentic workflows
• Students, hobbyists, or beginners interested in AI application development
Prerequisites
• Basic understanding of Python
• No prior experience with LLMs or LangChain needed — everything is taught step by step
By the End of This Course, You Will Be Able To:
• Confidently use LangChain to work with OpenAI and open-source models
• Structure and build LLM workflows using chains and tools
• Implement powerful features like RAG, chat history, and image understanding
• Deploy fully functional apps using Streamlit and LangChain
• Build your own intelligent apps using both cloud and local LLMs
If you’ve been wanting to learn how to work with LLMs in your own projects — using simple steps and real examples — this is the perfect course to get started.
Enroll now and bring your LLM ideas to life using LangChain.
Instructor Details
- 4.6 Rating
1,267 Reviews
Bharath Thippireddy
Bharath Thippireddy is an Entrepreneur, Software Architect, Author, Actor, and Public Speaker who has trained 950,000+ students across 209 countries.
He believes that learning is a crossing — from where you are to where you are capable of being. That belief drives every course he builds.
Bharath has mentored students and professionals across India and the USA — in classrooms, corporates, and agile conferences. He voluntarily teaches interview and soft skills at Vivekananda Kendra. He is the author of Hanuman's Leap, a book that takes the ancient wisdom of the Sundara Kanda and builds it into a complete framework for life's turning points. It comes out Diwali 2026 . He is currently completing his Executive MBA at the Indian School of Business.
He loves learning — in technology and in life — and shares everything he discovers.
From 50+ courses with 950,000+ learners, you can pick a track and master:
Generative AI — OpenAI, LangChain, LangGraph, Agentic AI with n8n, Azure OpenAI, GitHub Copilot
Spring Boot — full stack projects with Angular and React
Angular and React — with Java or Node backends
Python — core Python through Django REST Framework
DevOps and Cloud — Docker, Kubernetes, AWS EC2, Elastic Beanstalk, Jenkins, GIT, and more
Java — Design Patterns, Web Services, Messaging Service
Spring — Security, Boot, Data with Hibernate, Data REST
Serverless — AWS Lambda
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Reviews
By Deb Kumar Basu on 8/15/2026
This course is exactly what I was looking for. I am a Java developer who is familiar with python. Wanted to start my langchain training. This course looks to be tailor-made for me. Small code snippets, concise explanations, meaningful assignments and gradual prpogress. I am halfway and enjoying every bit of this course. Great work by the instructor!!
By Andrew Hollis on 3/13/2026
This was a great course. Explanations were clear and the instructor made all the topics feel very accessible. I feel like this was an excellent course to get introduced to the topic area. For future courses it might be helpful to include common mistakes and errors when implementing the code as well as alternative ways of doing the same thing. One of the challenges of building LLM apps is that there are multiple ways to accomplish something, but some ways are better than others. Instead of just providing one way (which the instructor does very well), maybe discuss other implementation strategies and compare and contrast. I know that will lengthen the course though. Just a suggestion though, overall, this course definitely accomplished what I was needing it to accomplish for me by introducing me to Langchain and AI app development in an accessible way.
By Rajan Santhanam on 12/22/2025
Best instructor! He explains tough concepts in a clear and concise way. I really love his teaching style. I always learn a lot from Bharath’s courses and feel confident applying the concepts to real‑world problems. I had previously taken his Django course and was able to successfully implement a full solution. I’m excited to continue learning and look forward to more content. I do have one recommendation: it would be great to have hands-on labs included with the course—perhaps using a code pad or similar interactive tools.
By Rajeev Ranjan on 10/6/2025
The instructor has an exceptional delivery style that effortlessly blends clarity with engagement. He use of well-chosen examples makes complex concepts easy to grasp, and his voice tone is incredibly soothing and captivating — it naturally keeps us wanting to listen more. His sessions feel less like lectures and more like insightful conversations, making learning both enjoyable and memorable.
By Ojas Teredesai on 8/20/2025
- This course offers a clear and structured introduction to LangChain, making it easy for developers to start building GenAI-powered applications. - I appreciated the hands-on walkthroughs, especially the use of OpenAI and open-source models like Mistral and Gemma via Ollama. - The explanation of PromptTemplates, LCEL, Chunks, Vectors was concise and practical, helping me apply these concepts in real projects. - Overall, this course accelerated my understanding of LangChain and gave me the confidence to architect intelligent LLM apps with clarity and purpose
By Edison Munoz Durango on 6/3/2025
It's definitely one of the best resources to learn about this technology. The content is perfectly structured, pedagogical, clear and concise, making it extremely easy to understand even for someone with zero prior knowledge. This course is absolutely useful and enriching; I've been able to acquire key skills that have directly helped me in my work as an engineer. The step-by-step teaching methodology has allowed me to build real projects without any hassle or confusion. Without a doubt, I would recommend it to anyone interested in GenAI and Langchain. It's truly a gem!
By Lokesh Rangineni on 5/30/2025
The course is very good as a beginner so it exceeded my expectations. It is very good course for the people who are already developers but new to langchain. Straight to the point and good hands on examples. The only improvement agent section is rough a bit more explanation or examples are needed. what kind of value it is adding over prompts. great course overall.
By Panagiotis Georgiadis on 4/24/2025
I would prefer items to be presented with a rationale, instead of sequentially. Explain first what we are aiming to do, and then show the steps we take towards achieving that goal.
By Venkata Gopal Wunnava on 11/23/2024
Installation of packages is an issue. Lots of dependencies need to be resolved based on version of python interpreter being used. It would be good for instructor to talk about that and provide some insight on troubleshooting.I had to research and fix all of that on my own for the langchain related packages.
By Anonymized User on 10/21/2024
Is is a very good course for beginner who just want to start with the langchain. If you could add more advanced contain or another course for advanced feature would be great. There are import which does not work with langchain 0.3.3 which needs to be mentioned. I was using azure open ai custom deployed model. The class used for that start with Azure like AzureChatOpenAI. If this thing are mentioned in the course then it would be flawless. I am really happy with the course.
Quality Score
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Overall Score : 92 / 100












