[NEW]Mastering Retrieval Augmented Generation (RAG) IN LLMs
What you'll learn
- Retrieval Augmented Generation (RAG) IN LLMs
- RAG using PDF
- RAG Using CSV file
- Laoding LLM Models
- Ollama
- Langchain
Requirements
- Python
- Generative AI basics
- Interest in GEN-AI
Description
In today's rapidly evolving landscape of artificial intelligence, Large Language Models (LLMs) have emerged as powerful tools for a wide range of applications. However, to truly unlock their full potential, we need to equip them with the ability to access and process external information. That's where Retrieval Augmented Generation (RAG) comes into play.
This course will provide you with a comprehensive understanding of RAG and its applications in enhancing LLM capabilities. You'll learn how to effectively retrieve relevant information from external sources and integrate it into the LLM's responses, making them more informative and accurate.
Course Objectives
Gain a solid understanding of generative AI and LLMs.
Explore the concept of RAG and its benefits.
Learn how to use Langchain to import and interact with LLMs.
Master the process of extracting context from PDFs and CSVs using Ollama.
Apply RAG techniques to enhance LLM performance in various tasks.
Course Structure
Introduction to Gen-AI using LLMs: This introductory lecture will provide a foundational understanding of generative AI and LLMs.
Introduction to RAG: Explore the concept of RAG, its benefits, and how it works.
Using Langchain to Import LLMs: Learn how to effectively import and interact with LLMs using the Langchain library.
Using Ollama to Extract Context from PDFs for LLM: Discover how to extract relevant information from PDFs and incorporate it into LLM responses.
Using Ollama to Extract Context from CSVs for LLM: Learn to extract context from CSV files and integrate it into LLM responses.
Why Choose This Course?
Practical Focus: Gain hands-on experience with RAG techniques and tools.
Expert Guidance: Learn from experienced instructors in the field of generative AI.
Comprehensive Coverage: Explore the entire RAG workflow from importing LLMs to extracting context.
Real-World Applications: Discover how RAG can be applied to various tasks and industries.
Enroll today and unlock the power of RAG to enhance your LLM applications!
Who this course is for:
- BEGINNER AI Developers
- data Scientists
- Analyst
- Python Developer
Instructor
- 4.1 Instructor Rating
- 963 Reviews
- 12,048 Students
- 13 Courses
I have done B.tech in Computer Science Engineering and 10 + years of experience as a professional instructor and trainer for Data Science and programming. During the course of my career I have developed a skill set in analyzing data and I love sharing my knowledge to help other people learn the power of programming, the ability to analyze data, as well as present the data in clear and beautiful visualizations.
I am a Data Scientist and have experience in python, Deep learning, NLP and Big Data. I provide in-person data science, Machine Learning and Deep Learning training to Data science enthusiasts with 0 to 30+ years of Experience. I believe in learning by doing, hence all of my courses will give an in-depth knowledge of concepts followed by detailed explanations of codes, tips and tricks which I have learnt over years. The sample problems and examples will allow you to explore more and give you enough practice to gain confidence at each and every concept. I am here to help you stay on the cutting edge of Data Science and Technology.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!