README.md

Additional resources

Here are links to other great resources to continue your learning and building with Generative AI.

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🧠 One Collection to Rule Them ALl

After completing this course, check out our Generative AI Learning collection to continue leveling up your Generative AI knowledge!

Lesson 1 - Introduction to Generative AI and LLMs

🔗 How GPT models work: accessible to everyone

🔗 Fundamentals of Generative AI

🔗 How GPT models work: accessible to everyone

🔗 Generative AI: Implication and Applications for Education

Lesson 2 - Exploring and Comparing Different LLM types

🔗 How to use Open Source foundation models curated by Azure Machine Learning (preview) - Azure Machine Learning | Microsoft Learn

🔗 The Large Language Model (LLM) Index | Sapling

🔗 [2304.04052] Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder (arxiv.org)

🔗 Retrieval Augmented Generation using Azure Machine Learning prompt flow

🔗 Grounding LLMs

🔗 The Large Language Model (LLM) Index | Sapling

🔗 [2304.04052] Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder (arxiv.org)

Lesson 3 - Using Generative AI Responsibly

🔗 Fundamentals of Responsible Generative AI

🔗 Grounding LLMs

🔗 Fundamentals of Responsible Generative AI

🔗 Being Responsible with Generative AI

🔗 GPT-4 System Card

Lesson 4 - Understanding Prompt Engineering Fundamentals

🔗 Getting Started with Azure OpenAI Services

Apply Prompt Engineering with Azure OpenAI services

Introduction to Prompt Engineering

🔗 Prompt Engineering Overview

🔗 Azure OpenAI for Education Prompts

🔗 Introduction to Prompt Engineering

🔗 Prompt Engineering Overview

🔗 Azure OpenAI for Education Prompts

Lesson 5 - Creating Advanced Prompts

🔗 Prompt Engineering Techniques

Lesson 6 - Building Text Generation Applications

🔗 Prompt Engineering Techniques

Lesson 7 - Building Chat Applications

🔗 System message framework and template recommendations for Large Language Models (LLMs)

🔗 Learn how to work with the GPT-35-Turbo and GPT-4 models

🔗 Fine-Tuning language models from human preferences

🔗 Build natural language solutions with Azure OpenAI Services

🔗 OpenAI Fine-Tuning

Lesson 8 - Building Search Applications

🔗 Azure Cognitive Search

🔗 OpenAI Embedding API

🔗 Cosine Similarity

Lesson 9 - Building Image Generation Applications

🔗 Generate Images with Azure OpenAI Service

🔗 OpenAI's DALL-E and CLIP 101: A Brief Introduction

🔗 OpenAI's CLIP paper

🔗 OpenAI's DALL-E and CLIP 101: A Brief Introduction

🔗 OpenAI's CLIP paper

Lesson 10 - Building Low Code AI Applications

🔗 Create bots with Microsoft Copilot Studio

🔗 Add intelligence with AI Builder and GPT

🔗 Get Started with AI Builder

🔗 Detect Objects with AI Builder

🔗 Build a canvas app solution with Copilot in Power Apps

🔗 Power Platform Copilot Prompt Library

Lesson 11- Integrating Applications with Function Calling

🔗 OpenAI Functions Documentation

Lesson 12 - Designing UX for AI Applications

🔗 Best practices for building collaborative UX with Human-AI partnership

🔗 Designing Human-Centric AI Experiences: Applied UX Design for Artificial Intelligence by Akshay Kpre

🔗 UX for AI: Design Practices for AI Developers

🔗 New skills in the age of AI by John Maeda

🔗 Designing Human-Centric AI Experiences: Applied UX Design for Artificial Intelligence by Akshay Kpre