What you'll learn:
- learn about the fundamentals of Azure OpenAI
- learn to integrate other Azure services with Azure OpenAI
- learn about generative AI
- becoming good at prompt engineering
- learn predictive AI (AI-102)
- learn about GitHub Copilot
- learn about securing Azure OpenAI
NOTE: This course is only for people interested in learning "Microsoft Azure OpenAIservice". If you are looking for open source version of OpenAI, then this course should not be on your wish list.
This course covers all the key concepts related to Azure OpenAI. Be it function calling or something as small as knowing how your engine processes tokens, the course has it all covered. In this course you will learn about concepts such as temperature parameter, token parameter, adding external API's to Azure Open AI function calling, integrating other Azure services such as the Azure Speech Service with Azure Open AI to make your engine/ model more efficient and powerful. This course is tailored in a very concise and short manner, providing you with only the important stuff so that your time is well-spent. This course will act as a bridge to your journey in being a master at using Azure Open AI and its offerings. Although this course is short, the course assures that you get your money's worth
Course Level: The course goes all the way up from level 0 to level 100; Don't know what's the basic difference between Azure OpenAI and OpenAI, don't worry, the course's got your back.
Hand-On Labs: The hands-on labs in the course are very enriching. You will be provided with a github repository which will contain all the codes for the hands-on labs covered in this course. The hands-on labs offered in this course cover a variety of topics including:
1) Chat Completions API.
2) Making use of text embedding engine for enhanced machine learning processes.
3) integrating speech-to-text token query retrieval in your chat engine.
4) making use of function calling functionality exclusive to Azure Open Ai to call an external API to retrieve real-time information/data.
5) Exploring concept of RAG (Retrieval Augmented Generation) by integrating Azure Ai Search with your chat engine.
6) Using Vector search and information retrieval using Azure Machine Learning Workspace.
7) Using GPT-4 using Computer Vision.
Bonus Section: A bonus section that includes GitHub Copilot has been made available with this course as well. Concepts like multi language support, @VScode agent, @workspace agent and code debugging have been explained in depth.
Prerequisites: knowledge about Python programming language and basic command line interface commands makes up for the prerequisites for the course.
Buy this course and get ready to embark on a journey full of brilliant learning.
