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Master LangChain & Gen AI -Build #16 AI Apps HuggingFace LLM (Udemy.com)

Learn End to End LLM Generative AI (Gen AI) projects - Langchain - OpenAI, HuggingFace, LLAMA 2 Gemin models Langchain

Created by: Sharath Raju

Last updated September 2026

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What you will learn

  • Develop Langchain based AI apps
  • Implement LLM powered apps
  • Learn Langchain from end to end
  • Complete project based approach

How it compares

Against the other 461 rated Udemy courses in Data Science on CourseDuck:

  • Rating4.7 out of 5higher than 85% of them
  • Reviews1,332#120 of 462 by number of reviews
  • Length10.2 hourslonger than 57% of them
  • Last updatedSeptember 2026more recently than 95% of them

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Course Description

Are you interested in harnessing the power of AI to create groundbreaking language-based applications?

Look no further than LangChain and Gen AI - a comprehensive course that will take you from a novice to an expert in no time.


Implement Generative AI (GenAI) apps with langchain framework using different LLMs.


By implementing AI applications powered with state-of-the-art LLM models like OpenAI and Hugging Face using Python, you will embark on an exciting project-based learning journey.


With LangChain, you will gain the skills and knowledge necessary to develop innovative LLM solutions for a wide range of problems.


Here are some of the projects we will work on:

Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces.

Project 2: Develop an engaging conversational bot using LangChain and OpenAI to deliver an interactive user experience.

Project 3: Create an AI-powered app tailored for children, facilitating the discovery of related classes of objects and fostering educational growth.

Project 4: Build a captivating marketing campaign app that utilizes the persuasive potential of well-crafted sales copy, boosting sales and brand reach.

Project 5: Develop a ChatGPT clone with an added summarization feature, delivering a versatile and invaluable chatbot experience.

Project 6: MCQ Quiz Creator App - Seamlessly create multiple-choice quizzes for your students using LangChain and Pinecone.

Project 7: CSV Data Analysis Toll - Helps you analyze your CSV file by answering your queries about its data.

Project 8: Youtube Script Writing Tool -  Effortlessly create compelling YouTube scripts with this user-friendly and efficient script-writing tool.

Project 9 - Support Chat Bot For Your Website - Helps your visitors/customers to find the relevant data or blog links that can be useful to them.

Project 10 - Automatic Ticket Classification Tool - The Automatic Ticket Classification Tool categorizes support tickets based on content to streamline ticket management and response processes.

Project 11 - HR - Resume Screening  Assistance - HR project using AI to assist in screening resumes, optimizing the hiring process with smart analysis and recommendations

Project 12 - Email Generator using LLAMA 2- The Email Generator is a tool that automatically creates customized emails, saving time and effort in crafting personalized messages.

Project 13 - Invoice Extraction Bot using LLAMA 2- Invoice Extraction Bot: AI-powered tool that extracts key details from invoices accurately and efficiently. Simplify your data entry process.

Project 14 - Text to SQL Query Helper Tool: Convert natural language text into structured SQL queries effortlessly using the Text to SQL Query Tool for streamlined database interaction and data retrieval.

Project 15 - Customer Care Call Summary Alert - Concise notification highlighting key points and outcomes from recent customer service calls, aiding quick understanding and response


This course is designed to provide you with a complete understanding of LangChain, starting from the basics and progressing toward creating practical LLM-powered applications.


LangChain empowers programmers to fully utilize large language models, such as ChatGPT, pinecone, LLAMA 2, and Huggingface, and seamlessly integrate them with external data sources. This integration enhances the models' ability to comprehend and respond to human language.


Built with Python, LangChain offers a user-friendly interface tailored specifically for beginners, making it accessible to aspiring developers.


Course Overview:

Aspiring to build sophisticated language-based applications

LangChain is the perfect library for you.

Move beyond basic techniques like keyword matching or rule-based systems and maximize your reach by langchain.

Leverage the power of LLMs, and applications using LangChain and combine them with cognitive or information sources & pinecone.

Unlock tremendous potential and explore new possibilities with applications using LangChain and Pinecone.


Course Contents:

LangChain

LLMs

Chat Models

Prompts

Indexes

Chains

Agents

Memory

Google Gemini Pro



But this isn't just a theory-based course; it's a hands-on experience. You will engage in practical activities and real-world projects, reinforcing your understanding of these concepts and techniques.


By the end of the course, you will be equipped with the skills to apply Langchain effectively, building robust, pinecone, powerful, and scalable LLM applications for various purposes.


Don't miss this opportunity to become a language model expert.

Enroll in the LangChain course and embark on a transformative journey that will elevate your AI app development skills. LangChain , OpenAI , ChatGPT , LLM, langchain pinecone , LLAMA 2 ,  Huggingface Google Gemini Pro Python - these are the tools that will empower you to create cutting-edge AI applications that push the boundaries of what's possible.


Get ready to unlock your full potential and become a hero in the world of language-based AI development through langchain.


You will do practical activities and real-world projects throughout the applications using LangChain pinecone Google Gemini Pro course to strengthen your understanding of the concepts and techniques.


You will be competent in applying Langchain pinecone to build strong, effective, and scalable LLM applications for a variety of uses by the end of the course.

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Instructor Details

Sharath Raju

I am an engineer by profession and by heart :)


It's been 8+ years since I have been working with software development, robotic process automation and AI app’s implementation.


I have implemented close to 80+ RPA processes in total by using Uipath & Microsoft Power Automate.


And also build AI powered apps using different technologies!


It is so true that someone learns more by not reading something but by practicing the skill.


I have been trying to understand exactly where people who are just starting out their career struggle and understand the pain of struggling for hours trying to figure something out.

I can help you with that.


Having a passion to share my piece of content, I have created step-by-step easy-to-digest courses.


My goal is to help you get ready for the future by learning new talents and becoming more productive by providing you with relevant and useful courses.


I'm still learning and exploring my field of work :)


Every feedback should be as valuable as you are to me, please feel free to reach out to me if you have any feedback, questions, or need any help. Thank You...

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Reviews

4.7

1,332 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Anonymized User on 7/29/2024

What a fantastic course this is for beginners! I am really thankful to the Sharath for such wonderful explanation and hand on LLM, LangChain, HuggingFace, Open AI models. I enjoyed this course by simultaneously implementing project on langchain.

By Togay Tunca on 7/13/2024

I really don't understand some of the low ratings. Comparing to some other courses on the subject matter the course is quite good. Although it is not comprehensive, I also like the integration explanations with Streamlit. But you may want to consider a separate short section on that. Good Job overall.

By Karan Sharma on 6/9/2024

very Good practical Examples/projects shown and explained without any hurry in each chapter. recommended for AI learners/beginners who wants to get an idea what all the buzz is about related to langchain, huggingface , OpenAI. More details/Examples can be added from huggingface point of view.

By Madhuri Chandanbatwe on 6/1/2024

Logic building for the code is not been shown,if you could integrate with what way we can approach the problem statement that would be great coz mostly the code is copy pasted and then explained,rather knowing how to approach and how to reach for the code of particular task

By Vishnuvardhan Kalathuru on 5/12/2024

Excellent Course. I took many lang chain courses, but this course really simplified the concepts and I'm able to connect the dots. RAG technique is explained in very simple manner and made it clear. Thank you.

By Divya teja on 5/10/2024

I would have given more stars if there is an option .It is really excellent session which helped to practice using the source code provided by the instructor .He explained very well on how we can use Open AI in developing the new models. I encourage fellow students to go through the course

By Ashish Gopal on 1/16/2024

One of the finest courses i have ever done in Udemy. Thank you. Just one thing, i could get this course for free in Youtube also, so that kinda hurts why to pay when u can get for free, apart from that the course was really great!

By Sudesh Agrawal on 1/14/2024

I recently embarked on a two-month-long journey in search of comprehensive insights into LangChain and its application development. After traversing various resources, I finally found my destination at LangChain, thanks to the exceptional guidance provided by the Sharath. I learrned everything whatever I was excepting

By 菅沼 重幸 on 10/31/2023

I am not native English speaker. I accessed this course from Japan. Even if so, this is very easy to understand and effective guide to create an AI applications. Thanks so much!

By Mohan Venkataraman on 8/20/2023

Course ware is good. There are issues in the imports and some of the logic. For example, I have been struggling with chain_type="stuff". The code worked once but in a second run gave issues. A bit of random hits like chain_type="refine", refine_prompt=QA_PROMPT works but .....

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Overall Score : 94 / 100