Roadmap to Learn Generative AI(LLM's) In 2024 With Free Videos And Materials- Krish Naik

Introduction

Hello everyone, my name is Krish Naik, and welcome to my YouTube channel! As we approach the new year, I often find myself evaluating the skill sets I want to acquire and share with you. My primary focus in 2023 has been on MLOps platforms, where I’ve developed numerous end-to-end projects and explored various tools beneficial for those aiming for a career transition into data science and MLOps. I believe that in 2024, especially with the rise of large language models (LLMs) and generative AI applications, mastering these skills will be crucial.

Focus on Generative AI

In recent months, my attention has shifted towards generative AI. The landscape is rapidly evolving with countless tools, frameworks, and models being introduced. Notably, we have seen the emergence of models such as Google’s Gemini and OpenAI’s GPT-4 Turbo, which are revolutionizing the way AI applications are developed. As a result, I will be dedicating 60-70% of my efforts to generative AI in 2024, while still maintaining a focus on MLOps platforms.

The Roadmap for 2024

In this video, I am excited to share an extensive roadmap designed specifically for those interested in generative AI in 2024. This roadmap is tailored for two types of profiles:

Individuals entering the data analytics industry or those looking to upgrade their skills.
Core developers interested in applying generative AI in their projects.

Completing the prerequisites outlined in this roadmap will give you a solid foundation to dive into generative AI.

Getting Started with Programming

The first step towards learning generative AI is mastering a programming language, and I highly recommend Python. The majority of LLM models available today, from Hugging Face to OpenAI, provide Python SDKs, enabling you to access APIs and deploy applications efficiently. I've created numerous Python tutorials accessible in both English and Hindi, which will be immensely beneficial.

Frameworks and Libraries

Once you're comfortable with Python, you can explore various frameworks like Flask and FastAPI. These frameworks are widely used for web application development and will be instrumental as you begin building generative AI applications. I've also made tutorials on other frameworks like Streamlit and Gradio to expand your programming toolkit.

Core Concepts in AI

Next on the roadmap is to gain a solid understanding of machine learning and natural language processing (NLP). Key concepts include:

Basic Machine Learning: Understanding algorithms essential for handling data effectively.
Natural Language Processing: Familiarizing yourself with techniques such as tokenization, embeddings (Word2Vec, TF-IDF), and basic concepts of deep learning.

Advanced NLP Concepts

Once you have a handle on the basics, you can transition to more advanced NLP topics, including:

Recurrent Neural Networks (RNN)
Long Short-Term Memory (LSTM)
Transformers

I have comprehensive playlist sessions that cover these advanced topics in detail, and I encourage you to explore these resources.

Open Source LLM Models

As you proceed, engage with open-source LLM models such as OpenAI's GPT, Hugging Face's offerings, and Google's models. Understanding their documentation will be key, and I will be sharing my insights through dedicated videos.

Deployment Strategies

Finally, learning how to deploy your projects using services such as AWS, Azure, and platforms supporting frameworks like LangChain will be crucial. My goal is to provide you with projects encompassing real-world use cases, which you can apply in various business scenarios.

Conclusion

To sum up, this roadmap emphasizes practical implementation of generative AI concepts, encourages continuous learning about emerging models, and supports developers and data analysts in building their expertise.

I invite you to check out the repository with all the links to videos, materials, and clear outlines of prerequisites required for a solid start in generative AI. Remember to keep an open mind, and be ready to embrace the innovations that 2024 will bring!

Keyword

Generative AI
Large Language Models (LLMs)
Python Programming
Machine Learning
Natural Language Processing (NLP)
Deep Learning Concepts
Advanced NLP
Open Source Models
Deployment Strategies
LangChain

FAQ

Q1: What is the main focus area for generative AI in 2024?
A1: The focus will be on understanding various frameworks, cloud platforms, and techniques in generative AI applications.

Q2: Is prior knowledge of programming necessary for beginners?
A2: Yes, a solid understanding of Python is crucial, but developers from other backgrounds can start with their core languages too.

Q3: What are the recommended prerequisites for learning generative AI?
A3: You'll need foundational knowledge in programming, machine learning, natural language processing, and deep learning concepts.

Q4: Where can I find free resources for learning generative AI?
A4: Complete playlists and tutorials are available on my YouTube channel, and a detailed repository containing links and necessary materials will be provided.

Q5: What frameworks should I learn for generative AI applications?
A5: Flask, FastAPI, Streamlit, and Gradio are recommended for starting with web applications in generative AI.