Azure Generative (OpenAI) + Predictive AI (23+ Hours)

Azure Generative (OpenAI) + Predictive AI (23+ Hours), available at $84.99, has an average rating of 4.43, with 218 lectures, based on 171 reviews, and has 2044 subscribers.

You will learn about 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 This course is ideal for individuals who are people curious about Azure OpenAI or developers looking to integrate intelligence of OpenAI in their products and services It is particularly useful for people curious about Azure OpenAI or developers looking to integrate intelligence of OpenAI in their products and services.

Enroll now: Azure Generative (OpenAI) + Predictive AI (23+ Hours)

Summary

Title: Azure Generative (OpenAI) + Predictive AI (23+ Hours)

Price: $84.99

Average Rating: 4.43

Number of Lectures: 218

Number of Published Lectures: 206

Number of Curriculum Items: 218

Number of Published Curriculum Objects: 206

Original Price: ?799

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

people curious about Azure OpenAI

developers looking to integrate intelligence of OpenAI in their products and services

Target Audiences

people curious about Azure OpenAI

developers looking to integrate intelligence of OpenAI in their products and services

NOTE: This course is only for people interested in learning “Microsoft Azure OpenAI service“. 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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Instructor Introduction

Lecture 2: Course Introduction

Chapter 2: Prerequisites

Lecture 1: Course Prerequisites

Lecture 2: Notice!

Lecture 3: Join The Discord Server

Chapter 3: Creating And Deploying Azure OpenAI Resource

Lecture 1: Caution: Things To Keep In Mind

Lecture 2: Creating an Azure OpenAI resource

Chapter 4: Chat Playground (For The Complete Beginners)

Lecture 1: Message!!

Lecture 2: Deployment

Lecture 3: Chatting With Our Model

Lecture 4: Using Dall-E

Lecture 5: Using GPT-4

Lecture 6: Chatting With Our GPT-4 Engine

Lecture 7: Deploying A Web App (Chat Engine) Using Your Own Data in 10 mins

Chapter 5: Prompt Engineering

Lecture 1: Prompts V/s Completions

Lecture 2: Prompts and Completions

Lecture 3: Refining Your Prompts

Lecture 4: Few Shot Learning And Chain Of Thoughts

Chapter 6: Chat Completions API

Lecture 1: Notice!!! GitHub Repo For C#

Lecture 2: Tokens

Lecture 3: Temperature

Lecture 4: Chat Completions API

Lecture 5: Lab Note

Lecture 6: lab1: Using Chat Completions API

Chapter 7: Important Concepts

Lecture 1: Difference between Azure OpenAI and OpenAI

Lecture 2: Azure OpenAi: Whats The Fuss

Lecture 3: What is Open AI?

Lecture 4: Is ChatGPT The New Google?

Lecture 5: Functions

Lecture 6: Lab Note

Lecture 7: lab: using functions in GPT engine

Lecture 8: What is Generative AI?

Lecture 9: Lab Note

Lecture 10: lab: keyword analysis with GPT engine

Lecture 11: Lab Note

Lecture 12: lab: Using GPT Engine As Your Code Buddy

Lecture 13: Lab Note

Lecture 14: Lab: Text Summarisation

Lecture 15: Understanding Generative Adversarial Networks (GANs)

Lecture 16: Difference between a ChatBot and Generative AI

Lecture 17: Predictive AI v/s Generative AI

Lecture 18: LLM V/s LAM

Chapter 8: The Synergistic Coexistence of Gen AI and Pred AI

Lecture 1: The Synergistic Coexistence of Gen AI and Pred AI

Chapter 9: Fine-Tuning Your Model

Lecture 1: Fine-Tuning Your Custom Model

Lecture 2: Caution

Lecture 3: Fine-Tuning Demo

Lecture 4: Evaluating Your Custom Model

Chapter 10: Jargons (small revision)

Lecture 1: Jargons

Lecture 2: Attention!!

Chapter 11: Whisper Model And Speech Service in OpenAI

Lecture 1: Understanding Whisper Model

Lecture 2: Lab Note

Lecture 3: Lab On Whisper Model via Azure OpenAI

Lecture 4: Lab Note

Lecture 5: lab: using AI speech service with GPT engine

Chapter 12: GPT 4 – The Talk Of The Town!

Lecture 1: Attention!!

Lecture 2: Introduction To GPT-4 engine

Lecture 3: Chat Playground Of GPT-4 engine

Lecture 4: Calling The GPT-4 Engine

Lecture 5: Lab Note

Lecture 6: Using GPT-4 Engine To Describe an Image

Lecture 7: Lab Note

Lecture 8: Integrating GPT-4 With Azure Vision Resource

Chapter 13: GPT-4o : The Best of The Rest

Lecture 1: Introduction to GPT-4o

Lecture 2: Chat Completions API with GPT-4o (Hands-On Lab)

Lecture 3: Image Analysis Using GPT-4o (Hand-On Lab)

Chapter 14: Working With Your Own Data

Lecture 1: What is RAG?

Lecture 2: Azure Machine Learning Vector Indexing

Lecture 3: Lab Note

Lecture 4: lab: using embedding engine

Lecture 5: Using GPT-4 alongwith Azure Machine Learning in ML Studio (RAG Lab)

Lecture 6: Vector Search With Azure Cognitive Search Theory

Lecture 7: Lab Note

Lecture 8: Hybrid Search (Vector + keyword search) With Azure Cognitive Search Lab

Lecture 9: RAG Pain Points

Lecture 10: Lab Note

Lecture 11: lab: Using Form Recognizer With GPT Engine

Chapter 15: Semantic Kernel: AI Orchestration Engine

Lecture 1: What Is Semantic Kernel?

Lecture 2: GitHub Repo for C#

Lecture 3: Plugins and Kernels

Lecture 4: Prompt Template Plugins

Lecture 5: Native Plugins

Lecture 6: Lab1: Getting Started (Hands-On) (Python)

Lecture 7: Lab1: Getting Started (Hands-On) (C#)

Lecture 8: Lab2: Exploring Prompt Template Plugins (Hands-On) (Python)

Lecture 9: Lab2: Exploring Prompt Template Plugins (Hands-On) (C#)

Instructors

Kuljot Singh Bakshi
Instructor at Udemy

Rating Distribution

1 stars: 7 votes

2 stars: 2 votes

3 stars: 16 votes

4 stars: 43 votes

5 stars: 103 votes

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