Generative AI for Business with Microsoft Azure OpenAI 

Module-1: Leveraging Generative AI for Business Applications

Week-1: ML Foundations for Generative AI

Mathematical Foundations of Generative AI

Understanding Machine Learning for Generative AI

Connect NLP fundamentals with advanced Generative AI applications

 

Week-2: Generative AI: Business Landscape & Overview

Understanding Generative and Discriminative AI

A brief timeline of Generative AI

A peek into generative models

Deconstructing the behavior of a large language models

ML, DL, and GenAI applications in business

Hands-on Demonstration of popular tools (ChatGPT & DALL-E)

 

Week-3: Prompt Engineering without Code

LLMs and the genesis of Prompting

How does the Attention Mechanism work

A brief history of the GPT model series

Accessing GPT through Azure

Designing prompts for business use cases using playground templates

Prompting techniques (Prompt templates, precise instructions, chain of thought prompting)

Ideating for prompts (prompt generation by induction, prompt paraphrasing)

Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models' performance.

Learn the capabilities of DALL-E in the Azure openAI service and Use the DALL-E playground in Azure OpenAI Studio

 

Week-4: Project: Product Feedback Review & Sentiment Analysis

 

Module-2: Python for Generative AI

Week-5: Python for Prompt Engineering : Part-1

Variables

Data types

Data Structures 

Conditions and Loops

Functions

Strings

Use natural language prompts to write code

 

Week-6: Python for Prompt Engineering: Part-2

Store text in Python

Edit, add, and delete text in Python

How to read files in Python

How to work with a database

Manipulate string columns

 

Week-7: Learning Break

 

Module-3: Designing Generative AI Solutions with Azure Open AI

Week-8: Prompt Engineering at Scale

Getting set with your Azure Open AI key and Python SDK

Completions and Chat API

Kinds of APIs, Models, Token, Rate Limits and Pricing

Evaluating Generative AI Outputs

Generate completions to prompts and begin to manage model parameters

Include clear instructions, request output composition, and use contextual content to improve the quality of the model's responses

 

Week-9: Classification Tasks with Generative AI

Framing text classification tasks as Generative AI problem

Sentiment classification

Assigning themes to a body of text 

Aspect-based sentiment analysis

 

Week-10: Content Generation and Summarization with Generative AI

Content generation using Generative AI 

Abstractive summarization

Text generation 

 

Week-11: Information Retrieval and Synthesis workflow with Gen AI

Overview of advanced application of Generative AI 

Understand information retrieval and synthesis workflow using Azure Open AI

Effectively communicate the core concepts of Retrieval-Augmented Generation (RAG) with the help of the LangChain package

Use Azure OpenAI API to generate responses based on your own data

 

Week-12: Final Project: Aspect-based Classification for Sentiment Analysis

 

Module-4: AI-900: Azure AI Fundamentals (Optional 4-week elective)

Week-13: Machine Learning workloads on Azure

Identify regression, classification, and clustering machine learning scenarios

Identify features and labels in a dataset for machine learning

Describe the capabilities of Automated machine learning

Describe data and compute services for data science and machine learning

Describe model management and deployment capabilities in Azure Machine Learning

 

Week-14: Computer Vision workloads on Azure

Identify common types of computer vision solution

Identify features of optical character recognition solutions

Capabilities of the Azure AI Vision service

Capabilities of the Azure AI Face detection service

 

Week-15: Natural Language workloads on Azure

Identify features and uses for key phrase extraction

Identify features and uses for entity recognition

Identify features and uses for language modeling

Identify features of common NLP Workload Scenarios

Identify Azure tools and services for NLP workloads

 

Week-16: Generative AI workloads on Azure

Identify features of generative AI solutions

Identify capabilities of Azure OpenAI Service