LLM and RAG | Updated with AI Agents (Udemy.com)
Build Web Applications Using LLMs and Streamlit | LangChain | Fine Tune the LLM | Retrieval Augmented Generation (RAG)
Created by: SeaportAi
Last updated January 2025
What you will learn
- Technology behind LLMs
- How to build an LLM programmatically
- How to fine tune an LLM
- How to build web based applications using LLM
- What is LangChain
- How to use LangChain in applications
- How to evaluate a large language model
- How to assess bias in an LLM
- How to fine tune GPT 3.5 easily
- What is RAG
- How does RAG differ from fine tuning
- What are the recent advances in RAG
- How to build a RAG application
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.1 out of 5higher than 9% of them
- Reviews48#1,119 of 1,183 by number of reviews
- Length2.8 hoursshorter than 73% of them
- Last updatedJanuary 2025earlier than 56% of them
Course Description
Welcome to a succinct and dynamic course tailored for individuals keen on diving into the world of Large Language Models (LLMs) and building custom applications. Whether you're a corporate IT professional concerned with data privacy or an AI enthusiast eager to leverage the power of LLMs, this course is designed for you!
Here’s a sneak peek of what we’ll explore:
Journey from NLP to LLMs:
Unveil the evolution from Natural Language Processing (NLP) to the advent of LLMs and understand the significance of this progression.
Technology Underpinning LLMs:
Delve into the core technologies driving LLMs including Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTMs) and Transformers.
Fine Tuning
Building LLM-based Web Applications:
Get hands-on with Streamlit and the OpenAI API to construct interactive web applications powered by LLMs.
Step-by-step guidance on crafting web applications for chatbots, engaging with PDF files, and summarizing web pages.
Building RAG applications
Introduction to LangChain:
Explore LangChain as a framework to further enhance your LLM application development experience.
Resources
All the codes and datasets used in the program are provided as downloadable resources.
Refresher on Core NLP:
A module for those wanting to brush up on the fundamentals of NLP to better grasp the advanced concepts presented.
This course is a living entity! As the field of LLMs evolves, so will the course material to ensure you stay updated with the latest advancements.
This course is perfectly suited for those aspiring to craft custom applications to harness the boundless potential of AI while being mindful of data privacy. Seize this opportunity to step into a world where language and technology intertwine seamlessly and embark on a learning journey that’s as engaging as it is enlightening!
Join us, as we unravel the mysteries of Large Language Models!
Instructor Details
- 4.1 Rating
48 Reviews
SeaportAi
Profile of Trainer Govind Kumar
Summary
. Over 2 decades of experience managing Technology, Operations and Quality in top MNCs & startups. Held leadership roles (including Founder & CEO of an AI Startup) and managed businesses across Asia Pacific & Japan region.
Expertise
. AI, Business Intelligence, Customer Experience, Six Sigma and Innovation
Key Experiences
. Successfully incubated Centers of Excellence for fraud prevention and service analytics.
. Significant experience in design thinking based product development and management. Played a critical role in developing products for emerging markets.
Education & Certification
. B. Tech (1993) and Full time MBA (1997) from top institutes in India
. Certifications in six sigma and project management.
Accolades
. Won global awards in the areas of Customer Experience, Leadership Excellence, Quality and Technology.
. Featured in the cover of CIO Review Magazine.
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Reviews
By Kaushal Kishore on 7/26/2025
Good Experience for Learning New in GEN AI
By Kuldeep Pandey on 6/19/2025
Too much theoretical. Could be better presented
By Alwin on 6/18/2024
Nice explanation
By Sampath on 5/20/2024
The course was very useful for me, the explanation was very clear and straight. I was glad to take up the course. When we have less idea about LLM, the detailed explanation gives better improvement. Thank you.
By Rajesh Haridoss on 5/16/2024
very theoretical, cant engage much in the training.
By Enrico Rubagotti on 5/3/2024
La version de openai used was the old one and the code did not run without substantial changes
By Archana Kumari on 6/19/2025
By Vivyek Kanchan on 4/25/2025
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 82 / 100












