- 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.
- LLM Bootcamp - Spring 2023 by The Full Stack
- DeepLearning AI
- Microsoft Copilot :- Microsoft Learn
- Amazon Generative AI
- Google Cloud - Cloud Skill Boost
- 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 |
| 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 |
| 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 |
| 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 |
| 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. |
| 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 |
| Course Title | Description | Link |
|---|---|---|
| RAG From Scratch - Amazing Tutorial by LangChain | Youtube videos |  |
| 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 | |