Course Information
Course Overview
Learn GenAI, LLM, Langchain, Prompt Engineering in a project based approach
This course is a practical guide to learning Generative AI concepts:
- Large Language Models
- Tokenization, Word Vectors and Embeddings
- Fine tuning LLMs
- Langchain
- Prompt Enginnering concepts
- Using OpenAI API
The field of artificial intelligence has seen incredible advances in recent years, with one area gaining significant traction - generative AI. This cutting-edge technology is poised to revolutionize how we create and interact with all kinds of digital content.
So, What exactly is generative AI? At its core, it refers to AI models that can generate new data, rather than just analyzing existing data. This could include generating text, images, audio, video, computer code, and more - often starting from just a basic prompt or input from a user. What makes this technology so powerful is how user-friendly it is becoming. You can simply describe a scene or concept, and the AI model generates high-quality digital content in response - almost like magic!
1. Artificial Intelligence:
This prime spot is reserved for just plain AI. It's a broad term, the overarching goal: machines that mimic human intelligence. That includes everything from playing chess to diagnosing diseases, from composing music to writing this blog.
2. Machine Learning:
Machine Learning (ML), a subset of AI. It's where the magic of learning from data happens. ML algorithms don't need explicit programming – they gobble up data, identify patterns, and improve their performance over time.
3. Deeper and Deeper: When ML Gets Fancy - Deep Learning
This is ML on steroids, using complex artificial neural networks loosely inspired by the human brain. Deep learning is the secret sauce behind many of AI's recent breakthroughs, allowing for crazy-powerful stuff like image and speech recognition.
4. Generative AI
This is the elephant baby of the AI world or the rebellious teenager with a paintbrush. It uses machine learning to create entirely new content, from composing electronic dance music symphonies to generating hyperrealistic images of, well, anything you can imagine (including, unfortunately, deepfakes so convincing they'd make our grandma believe the orange cats can dance).
Course Content
- 4 section(s)
- 27 lecture(s)
- Section 1 Introduction
- Section 2 LLM Fine Tuning Arc
- Section 3 Prompt Engineering
- Section 4 Major Project: Building a PDF Chatbot
What You’ll Learn
- Fine tuning an LLM
- Prompt Engineering
- Gen AI Basics
- OpenAI API Usage
- Langchain Basics
Reviews
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ZZubin Talavia
It was good overview but the coding exercises were too fast for me to keep up given that I have not coded in years. Maybe spend more time on setting up the environment and give us guidelines on using the coding techniques etc would help. Like Coding for Dummies
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CChandru Karthikeyan
Good content
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JJeeva Roshini S K
Some software used in the video are in their older version
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TTarit Das
It was overall good, but the mentor could be more specific as most of the people who are learning they dont know python and other llm tools, he was doing but not explaining who it is so.