⭐ GenAI-Learning

• AI Engineers possess a good understanding of programming, software engineering, and data science, and use different tools and techniques to process data and to develop and maintain AI systems.

Table of Contents

1. LLM Bootcamp - Spring 2023 by The Full Stack
2. DeepLearning AI
3. Microsoft Copilot :- Microsoft Learn
4. Amazon Generative AI
5. Google Cloud - Cloud Skill Boost
6. NVDIA Learn
7. Oracle Cloud
8. IBM AI Learn

LLM Bootcamp - Spring 2023 by The Full Stack

• Full Stack LLM Bootcamp
  • Learn best practices and tools for building LLM-powered apps
  • Cover the full stack from prompt engineering to user-centered design
  • Get up to speed on the state-of-the-art

Course Name	Description	Link
Launch an LLM App in One Hour	Brief overview of the course content	Course Link
LLM Foundations	Introduction to the basics of LLMs	Course Link
Learn to Spell: Prompt Engineering	Techniques for effective prompting	Course Link
Augmented Language Models	Enhancing LLMs with tools and data	Course Link
Project Walkthrough: askFSDL	Step-by-step guide for the project	Course Link
UX for Language User Interfaces	Designing intuitive LLM interactions	Course Link
LLMOps	Deployment and management of LLM solutions	Course Link
What's Next?	Future directions in LLM development	Course Link
Reza Shabani: How to train your own LLM	Deep dive into LLM training	Course Link
Harrison Chase: Agents	Building LLM-powered agents	Course Link
Fireside Chat with Peter Welinder	Insights from an industry leader	Course Link

DeepLearning AI

Course Title	Description	Link
AI for Everyone	AI is not only for engineers. “AI for Everyone”, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today’s AI can – and cannot – do.	Course Link
Generative AI for Everyone	Learn how generative AI works, and how to use it in your life and at work	Course Link
Learn the fundamentals of generative AI for real-world applications	In Generative AI with Large Language Models (LLMs), created in partnership with AWS, you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.	Course Link
Machine Learning Engineering for Production (MLOps) Specialization	The Machine Learning Engineering for Production (MLOps) Specialization covers how to conceptualize, build, and maintain integrated systems that continuously operate in production. In striking contrast with standard machine learning modeling, production systems need to handle relentless evolving data	Course Link

Prompt Engineering

Course Title	Description	Link
ChatGPT Prompt Engineering for Developers by DeepLearning.AI	Learn to leverage ChatGPT for application development	Course link
Prompt Engineering with Llama 2	Explore prompt design for the open-source Llama 2 model	Course link
Master Prompt Engineering by Prompt Engineering Institute	Comprehensive course on LLM prompting from marketing experts	Course link
Introductory Course on Prompt Engineering by LearnPrompting	Beginner-friendly introduction to prompt engineering concepts	Website link:
The Prompt Engineering Guide	A detailed resource for mastering prompt creation	Website link

Retrieval-Augmented Generation

Course Title	Description	Link
RAG From Scratch - Amazing Tutorial by LangChain
RAGHack 2024
RAG (Retrieval Augmented Generation)
Master RAG in 5 Hrs

YouTube Free Courses

Course Title	Channel Name	Link
AI 4 Every 1 - Learn the Modern Artificial Intelligence from Scratch	Murtaza's Workshop - Robotics and AI
Generative AI Full Course	Freecodecamp
Gen AI Course Gen AI Tutorial For Beginners	Codebasics
Introduction to large language models	IIT Madras BS Degree
Genartive AI News	Krish Naik
Introduction to large language models	IIT Madras BS Degree
LLM Crash Course	Neural Hacks with Vasanth
Genartive AI	Sunny Savita
DeepLearningAI	DeepLearningAI
Generative AI Hands-on Course – OpenAI, Gemini Pro, Llama 3, Ollama, Langchain, RAG & More	Siddhardhan
Microsoft Developer	Full Series Generative AI for Beginners

Other Github links

Material Type
Indepth-GENAI
Next-Genarative-AI-courses-by-campusx
Building-LLM-Powered-Applications Book

7 GitHub Repo to Master GenerativeAI

Title	Link
1. Generative AI for Beginners - Microsoft	https://github.com/microsoft/generative-ai-for-beginners
2. GenerativeAI by Google Cloud Platform	https://github.com/GoogleCloudPlatform/generative-ai
3.Awesome Generative AI	https://github.com/steven2358/awesome-generative-ai
4. Awesome GenAI	https://github.com/filipecalegario/awesome-generative-ai
5. Learn Generative AI	https://github.com/panaverse/learn-generative-ai
6. Generative AI Research Papers Collection	https://github.com/kevinknights29/GenAI_Papers
7. GenerativeAI Projects	https://github.com/yagyesh-bobde/GenAI-Projects
8. Awesome-RAG	https://github.com/lucifertrj/Awesome-RAG

Google Cloud - Cloud Skill Boost

Course Name	Description	Link
Introduction to Generative AI	This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.	Course Link
Introduction to Large Language Models	This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.	Course Link
Introduction to Responsible AI	This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 7 AI principles.	Course Link
Prompt Design in Vertex AI	Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.	Course Link
Responsible AI: Applying AI Principles with Google Cloud	As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.	Course Link
Introduction to Image Generation	This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud.	Course Link
Attention Mechanism	This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering.	Course Link
Encoder-Decoder Architecture	This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.	Course Link
Transformer Models and BERT Model	This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.	Course Link
Create Image Captioning Models	This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images	Course Link
Introduction to Generative AI Studio	This course introduces Generative AI Studio, a product on Vertex AI, that helps you prototype and customize generative AI models so you can use their capabilities in your applications. In this course, you learn what Generative AI Studio is, its features and options, and how to use it by walking through demos of the product. In the end, you will have a quiz to test your knowledge	Course Link
Generative AI Explorer - Vertex AI	The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more.	Course Link
Explore and Evaluate Models using Model Garden	Model Garden on Vertex AI provides a single place to search, discover, and interact with a wide variety of models from Google and Google partners. Model Garden is available on Vertex AI and can be accessed from the Google Cloud console.	Course Link
Prompt Design using PaLM	Prompt design is the process of creating prompts that are effective in generating the desired output from a large language model (LLM) like PaLM. Prompts can be used to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.	Course Link

Microsoft Copilot :- Microsoft Learn

Course Title	Description	Link
Intro to Python for Data Science	Foundational Python skills for data manipulation	Course Link
Build AI Solutions with Azure Machine Learning	Using Azure ML for development, including potential GenAI	Course Link
Responsible AI Principles	Ethical considerations in AI development	Course Link
Using Azure OpenAI Service	Get started with generative AI, copilots, large language models, and Azure OpenAI Service.	Course Link
AI for Beginners	12-week, 24-lesson curriculum exploring AI.	Course Link
Create custom Machine Learning models	Work with Azure Machine Learning to create machine learning models. Explore the workspace, work with data, and automate machine learning model selection	Course Link
Build apps with Azure AI services and Power Virtual Agents	Start your AI learning journey with Azure AI Services. Find resources on Azure OpenAI and learn how to fine-tune advanced language models from OpenAI.	Course Link
Master Azure AI fundamentals	Explore machine learning, computer vision, natural language processing, decision support, and knowledge mining, all while getting ready to earn your next credential.	Course Link
GitHub Copilot for Visual Studio	Find out how to use AI every day to streamline your work with GitHub Copilot. This content is recommended for developers.	Course Link
Adopting Copilot for Microsoft 365	Discover the benefits of adopting Copilot for Microsoft 365. Learn about its versatility, streamline communication, and power up content creation.	Course Link

Amazon Generative AI

Course Name	Description
Generative AI Foundations on AWS¹	A technical deep dive course that gives you the conceptual fundamentals, practical advice, and hands-on guidance to pre-train, fine-tune, and deploy state-of-the-art foundation models on AWS and beyond.
Amazon CodeWhisperer – Getting Started²	A free, self-paced digital course introducing learners to Amazon CodeWhisperer, an AI coding companion designed to help developers get more done, faster.
AWS Jam Journey – Build Using Amazon CodeWhisperer²	A course that helps developers use Amazon CodeWhisperer effectively.
Foundations of Prompt Engineering³	A course that provides a foundation for prompt engineering in Generative AI.
Low-Code Machine Learning on AWS³	A course that introduces low-code machine learning on AWS.
Building Language Models on AWS³	A course that guides you through building language models on AWS.
Amazon Transcribe — Getting Started³	A course that introduces Amazon Transcribe, a service that converts speech into text.
Building Generative AI Applications Using Amazon Bedrock³	A course that guides you through building Generative AI applications using Amazon Bedrock.

Oracle Learning Path Resources

Course Title	Description	Link
Become an OCI Generative AI Professional	A comprehensive learning path to gain expertise in Oracle Cloud Infrastructure (OCI) Generative AI.	Oracle Learning Path
Become an OCI AI Foundations Associate (2024)	Foundational course for understanding AI concepts and OCI AI services, tailored for 2024 curriculum.	Oracle Learning Path