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

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: What's 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#)