How to begin learning technologies for Generative AI and LLMs?

If you looking for programming language to start with, then I would highly recommend to get comfortable and starting working on Python. ML and AI tools are heavily built using Python. Python is quite intuitive and less verbose to begin. It has extensive support of libraries to built anything and everything you can imagine. The community of python is great and lot of open source projects are available for people to learn.

Learning Python

1. Python for Everybody (Coursera)

   • A comprehensive course by Dr. Charles Severance that covers the basics of Python programming. Great for beginners.

   • Course Link

2. Automate the Boring Stuff with Python (YouTube)

   • A practical guide to using Python to automate daily tasks. Based on the popular book by Al Sweigart. : YouTube Link

3. Python Crash Course (YouTube by Mosh Hamedani)

   • An engaging crash course covering Python basics, ideal for beginners wanting a fast-track introduction. : YouTube Link

4. The Python Tutorial (Official Documentation)

   • The official Python tutorial, perfect for getting a deep understanding straight from the source: Documentation Link

Basics About Large Language Models (LLMs)

It is important to understand what are LLMs from first principle to know what the hype is all about. Learnings basics of LLms will give an insight into how we reached here and what path was followed.

1. Introduction to Large Language Models (Google Cloud)

   • An introductory course that explains the basics of LLMs, their architecture, and applications. : Course Link

2. Understanding Large Language Models (YouTube by Andrej Karpathy)

   • A detailed video that breaks down the complex concepts behind LLMs, making them accessible. : YouTube Link

3. The Illustrated GPT-3 (Blog by Jay Alammar)

   • A visual and intuitive explanation of how GPT-3, one of the most famous LLMs, works. : Blog Link

4. Stanford's CS224N: Natural Language Processing with Deep Learning (Lecture Videos)

   • A series of lecture videos that cover the fundamentals of NLP and LLMs, suitable for students with some background in machine learning. : YouTube Link

OpenAI Tutorials

1. OpenAI API Quickstart Guide (Official)

   • A quickstart guide by OpenAI that helps you set up and start using their API for various applications : Quickstart Link

2. OpenAI GPT-3 Sandbox (YouTube by Nicholas Renotte)

   • A hands-on tutorial on using the GPT-3 Sandbox to build and test applications : YouTube Link

3. Building a Chatbot with OpenAI (Medium)

   • A detailed tutorial on Medium about building a chatbot using OpenAI's GPT-3 API.

LangChain Tutorials

LangChain is an open-source Python framework that helps developers build applications using large language models (LLMs). LLMs are deep-learning models that are pre-trained on large amounts of data and can respond to user queries. LangChain provides tools and components to simplify the development of LLM-based applications, and to improve the accuracy and relevance of the information they generate.

1. LangChain Documentation (Official)

   • The official documentation provides comprehensive guides and examples to help you get started with LangChain. : Documentation Link

2. Building Applications with LangChain (YouTube by Data School)

   • A video tutorial series that walks through building various applications using LangChain. : YouTube Link

3. LangChain Tutorial (Medium)

   • A step-by-step tutorial on Medium that introduces the basics of using LangChain in practical scenarios.

4. LangChain for Beginners (GitHub Repository)

   • A GitHub repository with sample projects and tutorials to help beginners get started with LangChain : GitHub Link

Industry Experts to Follow

1. Andrew Ng

   • Twitter: @AndrewYNg

   • Founder of deeplearning.ai and Coursera, a leading figure in AI and machine learning education.

2. Yann LeCun

   • Twitter: @ylecun

   • Chief AI Scientist at Facebook and a pioneer in the field of deep learning and convolutional networks.

3. Fei-Fei Li

   • Twitter: @drfeifei

   • Co-Director of the Stanford Human-Centered AI Institute and an influential researcher in AI and computer vision.

4. Sebastian Ruder

   • Twitter: @seb_ruder

   • Research Scientist at DeepMind, known for his work in NLP and machine learning.

These resources and experts will provide a solid foundation and keep you updated with the latest trends and advancements in Python, LLMs, LangChain, and OpenAI. Happy learning!