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⭐ πŸ”– awesome-generative-ai-guide

Generative AI is experiencing rapid growth, and this repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more!

aishwaryanr%2Fawesome-generative-ai-guide | Trendshift

Explore the following resources:

  1. Monthly Best GenAI Papers List
  2. GenAI Interview Resources
  3. Applied LLMs Mastery 2024 (created by Aishwarya Naresh Reganti) course material
  4. Generative AI Genius 2024 (created by Aishwarya Naresh Reganti) course material
  5. List of all GenAI-related free courses (over 90 listed)
  6. List of code repositories/notebooks for developing generative AI applications

We'll be updating this repository regularly, so keep an eye out for the latest additions!

Happy Learning!


⭐ Top AI Tools List

Discover our favorite AI tools spanning every layer of AI application development. Click here to learn more.


πŸ”ˆ Announcements


πŸŽ“ Courses

[Ongoing] Applied LLMs Mastery 2024

Join 1000+ students on this 10-week adventure as we delve into the application of LLMs across a variety of use cases

Link to the course website

[Feb 2024] Registrations are still open click here to register

πŸ—“οΈ*Week 1 [Jan 15 2024]*: Practical Introduction to LLMs

  • Applied LLM Foundations
  • Real World LLM Use Cases
  • Domain and Task Adaptation Methods

πŸ—“οΈ*Week 2 [Jan 22 2024]*: Prompting and Prompt Engineering

  • Basic Prompting Principles
  • Types of Prompting
  • Applications, Risks and Advanced Prompting

πŸ—“οΈ*Week 3 [Jan 29 2024]*: LLM Fine-tuning

  • Basics of Fine-Tuning
  • Types of Fine-Tuning
  • Fine-Tuning Challenges

πŸ—“οΈ*Week 4 [Feb 5 2024]*: RAG (Retrieval-Augmented Generation)

  • Understanding the concept of RAG in LLMs
  • Key components of RAG
  • Advanced RAG Methods

πŸ—“οΈ*Week 5 [ Feb 12 2024]*: Tools for building LLM Apps

  • Fine-tuning Tools
  • RAG Tools
  • Tools for observability, prompting, serving, vector search etc.

πŸ—“οΈ*Week 6 [Feb 19 2024]*: Evaluation Techniques

  • Types of Evaluation
  • Common Evaluation Benchmarks
  • Common Metrics

πŸ—“οΈ*Week 7 [Feb 26 2024]*: Building Your Own LLM Application

  • Components of LLM application
  • Build your own LLM App end to end

πŸ—“οΈ*Week 8 [March 4 2024]*: Advanced Features and Deployment

  • LLM lifecycle and LLMOps
  • LLM Monitoring and Observability
  • Deployment strategies

πŸ—“οΈ*Week 9 [March 11 2024]*: Challenges with LLMs

  • Scaling Challenges
  • Behavioral Challenges
  • Future directions

πŸ—“οΈ*Week 10 [March 18 2024]*: Emerging Research Trends

  • Smaller and more performant models
  • Multimodal models
  • LLM Alignment

πŸ—“οΈ*Week 11 *Bonus* [March 25 2024]*: Foundations

  • Generative Models Foundations
  • Self-Attention and Transformers
  • Neural Networks for Language

πŸ“– List of Free GenAI Courses

LLM Basics and Foundations
  1. Large Language Models by ETH Zurich

  2. Understanding Large Language Models by Princeton

  3. Transformers course by Huggingface

  4. NLP course by Huggingface

  5. CS324 - Large Language Models by Stanford

  6. Generative AI with Large Language Models by Coursera

  7. Introduction to Generative AI by Coursera

  8. Generative AI Fundamentals by Google Cloud

  9. 5-Day Gen AI Intensive Course by Google & Kaggle

  10. Introduction to Large Language Models by Google Cloud

  11. Introduction to Generative AI by Google Cloud

  12. Generative AI Concepts by DataCamp (Daniel Tedesco Data Lead @ Google)

  13. 1 Hour Introduction to LLM (Large Language Models) by WeCloudData

  14. LLM Foundation Models from the Ground Up | Primer by Databricks

  15. Generative AI Explained by Nvidia

  16. Transformer Models and BERT Model by Google Cloud

  17. Generative AI Learning Plan for Decision Makers by AWS

  18. Introduction to Responsible AI by Google Cloud

  19. Fundamentals of Generative AI by Microsoft Azure

  20. Generative AI for Beginners by Microsoft

  21. ChatGPT for Beginners: The Ultimate Use Cases for Everyone by Udemy

  22. [1hr Talk] Intro to Large Language Models by Andrej Karpathy

  23. ChatGPT for Everyone by Learn Prompting

  24. Large Language Models (LLMs) (In English) by Kshitiz Verma (JK Lakshmipat University, Jaipur, India)

  25. Generative AI for Beginners By CodeKidz, based on Microsoft's open sourced course.

Building LLM Applications
  1. LLMOps: Building Real-World Applications With Large Language Models by Udacity

  2. Full Stack LLM Bootcamp by FSDL

  3. Generative AI for beginners by Microsoft

  4. Large Language Models: Application through Production by Databricks

  5. Generative AI Foundations by AWS

  6. Introduction to Generative AI Community Course by ineuron

  7. LLM University by Cohere

  8. LLM Learning Lab by Lightning AI

  9. LangChain for LLM Application Development by Deeplearning.AI

  10. LLMOps by DeepLearning.AI

  11. Automated Testing for LLMOps by DeepLearning.AI

  12. Building Generative AI Applications Using Amazon Bedrock by AWS

  13. Efficiently Serving LLMs by DeepLearning.AI

  14. Building Systems with the ChatGPT API by DeepLearning.AI

  15. Serverless LLM apps with Amazon Bedrock by DeepLearning.AI

  16. Building Applications with Vector Databases by DeepLearning.AI

  17. Automated Testing for LLMOps by DeepLearning.AI

  18. Build LLM Apps with LangChain.js by DeepLearning.AI

  19. Advanced Retrieval for AI with Chroma by DeepLearning.AI

  20. Operationalizing LLMs on Azure by Coursera

  21. Generative AI Full Course – Gemini Pro, OpenAI, Llama, Langchain, Pinecone, Vector Databases & More by freeCodeCamp.org

  22. Training & Fine-Tuning LLMs for Production by Activeloop

Prompt Engineering, RAG and Fine-Tuning
  1. LangChain & Vector Databases in Production by Activeloop

  2. Reinforcement Learning from Human Feedback by DeepLearning.AI

  3. Building Applications with Vector Databases by DeepLearning.AI

  4. Finetuning Large Language Models by Deeplearning.AI

  5. LangChain: Chat with Your Data by Deeplearning.AI

  6. Building Systems with the ChatGPT API by Deeplearning.AI

  7. Prompt Engineering with Llama 2 by Deeplearning.AI

  8. Building Applications with Vector Databases by Deeplearning.AI

  9. ChatGPT Prompt Engineering for Developers by Deeplearning.AI

  10. Advanced RAG Orchestration series by LlamaIndex

  11. Prompt Engineering Specialization by Coursera

  12. Augment your LLM Using Retrieval Augmented Generation by Nvidia

  13. Knowledge Graphs for RAG by Deeplearning.AI

  14. Open Source Models with Hugging Face by Deeplearning.AI

  15. Vector Databases: from Embeddings to Applications by Deeplearning.AI

  16. Understanding and Applying Text Embeddings by Deeplearning.AI

  17. JavaScript RAG Web Apps with LlamaIndex by Deeplearning.AI

  18. Quantization Fundamentals with Hugging Face by Deeplearning.AI

  19. Preprocessing Unstructured Data for LLM Applications by Deeplearning.AI

  20. Retrieval Augmented Generation for Production with LangChain & LlamaIndex by Activeloop

  21. Quantization in Depth by Deeplearning.AI

Evaluation
  1. Building and Evaluating Advanced RAG Applications by DeepLearning.AI
  2. Evaluating and Debugging Generative AI Models Using Weights and Biases by Deeplearning.AI
  3. Quality and Safety for LLM Applications by Deeplearning.AI
  4. Red Teaming LLM Applications by Deeplearning.AI
Multimodal
  1. How Diffusion Models Work by DeepLearning.AI
  2. How to Use Midjourney, AI Art and ChatGPT to Create an Amazing Website by Brad Hussey
  3. Build AI Apps with ChatGPT, DALL-E and GPT-4 by Scrimba
  4. 11-777: Multimodal Machine Learning by Carnegie Mellon University
  5. Prompt Engineering for Vision Models by Deeplearning.AI
Agents
  1. Building RAG Agents with LLMs by Nvidia
  2. Functions, Tools and Agents with LangChain by Deeplearning.AI
  3. AI Agents in LangGraph by Deeplearning.AI
  4. AI Agentic Design Patterns with AutoGen by Deeplearning.AI
  5. Multi AI Agent Systems with crewAI by Deeplearning.AI
  6. Building Agentic RAG with LlamaIndex by Deeplearning.AI
  7. LLM Observability: Agents, Tools, and Chains by Arize AI
  8. Building Agentic RAG with LlamaIndex by Deeplearning.AI
  9. Agents Tools & Function Calling with Amazon Bedrock (How-to) by AWS Developers
  10. ChatGPT & Zapier: Agentic AI for Everyone by Coursera
  11. Multi-Agent Systems with AutoGen by Victor Dibia [Book]
  12. Large Language Model Agents MOOC, Fall 2024 by Dawn Song & Xinyun Chen – A comprehensive course covering foundational and advanced topics on LLM agents.
  13. CS294/194-196 Large Language Model Agents by UC Berkeley

Miscellaneous

  1. Avoiding AI Harm by Coursera
  2. Developing AI Policy by Coursera

πŸ“Ž Resources


πŸ’» Interview Prep

Topic wise Questions:

  1. Common GenAI Interview Questions
  2. Prompting and Prompt Engineering
  3. Model Fine-Tuning
  4. Model Evaluation
  5. MLOps for GenAI
  6. Generative Models Foundations
  7. Latest Research Trends

GenAI System Design (Coming Soon):

  1. Designing an LLM-Powered Search Engine
  2. Building a Customer Support Chatbot
  3. Building a system for natural language interaction with your data.
  4. Building an AI Co-pilot
  5. Designing a Custom Chatbot for Q/A on Multimodal Data (Text, Images, Tables, CSV Files)
  6. Building an Automated Product Description and Image Generation System for E-commerce

πŸ““ Code Notebooks

RAG Tutorials

Fine-Tuning Tutorials

Comprehensive LLM Code Repositories

  • LLM-PlayLab This playlab encompasses a multitude of projects crafted through the utilization of Transformer Models

βœ’οΈ Contributing

If you want to add to the repository or find any issues, please feel free to raise a PR and ensure correct placement within the relevant section or category.


πŸ“Œ Cite Us

To cite this guide, use the below format:

@article{areganti_generative_ai_guide,
author = {Reganti, Aishwarya Naresh},
journal = {https://github.com/aishwaryanr/awesome-generative-ai-resources},
month = {01},
title = {{Generative AI Guide}},
year = {2024}
}

License

[MIT License]

** This section is sponsored. We do not endorse or guarantee the product/service and are not responsible for any issues arising from its use. Please evaluate and use at your discretion.

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