Mastering Generative AI through OpenAI Hands-On

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to AI in Retail

Lecture 2: Artificial Intelligence and related fields

Lecture 3: How AI can unlock value

Lecture 4: Understanding Generative AI: Concepts and Evolution

Lecture 5: Understanding Autoencoders

Lecture 6: Variational Auto Encoders

Lecture 7: Understanding Generative Adversarial Networks – GANs

Lecture 8: Gen AI Use Cases and High Level Walkthrough

Lecture 9: How Walmart is Harnessing GenAI Power (based on information in public domain)

Lecture 10: Ethical consideration

Lecture 11: Challenges for using AI in Retail

Chapter 2: Introduction to Machine Learning

Lecture 1: Introduction to Machine Learning Algorithms

Lecture 2: Understanding Machine Learning Process

Lecture 3: Data Processing in Machine Learning

Chapter 3: Understanding Gen AI

Lecture 1: Understanding Gen AI and LLM

Lecture 2: Definition and Background of GPT

Lecture 3: Features of ChatGPT

Lecture 4: Models from OpenAI – GPT

Lecture 5: Working with GPT API

Lecture 6: ChatGPT v Playground and include discussion on Davinchi Model, Tokens, temeperat

Lecture 7: ChatGPT architecture (how to build such a model)

Lecture 8: Understanding Transformers

Chapter 4: Prompt Engineering

Lecture 1: How to create better prompts

Lecture 2: Asking for Facts and Details

Lecture 3: Asking for Suggestions

Lecture 4: Doing Language Translation

Lecture 5: Using for Comparison

Lecture 6: Creative Writing

Lecture 7: Brainstorming ideas for you

Lecture 8: List Generation

Lecture 9: Summarizing content

Lecture 10: Generate list of Pros and Cons

Lecture 11: Get Quotes on your topic

Lecture 12: Access research studies

Lecture 13: Feedback on your content

Lecture 14: Role playing with ChatGPT

Lecture 15: Explanation of Concepts

Lecture 16: Writing programs

Lecture 17: Using chatGPT as a mentor

Lecture 18: Creating engaging presentations

Lecture 19: Working with Excel formulae

Lecture 20: Generating sample data using ChatGPT

Lecture 21: Conclusion

Chapter 5: Understanding the Components of Generative AI

Lecture 1: What is RAG

Lecture 2: Understanding LangChain

Lecture 3: Using LangChain for Retail Operations

Chapter 6: Building Gen AI Use Cases Hands-On

Lecture 1: Speak out loud application

Lecture 2: Build language translator web app

Lecture 3: Generate Product Description

Lecture 4: Developing Chatbots for AI-driven Customer Interactionn using Langchain

Lecture 5: Generating Synthetic Data – Demand Forecasting Data

Lecture 6: Working with Inventory Data

Chapter 7: Implementation

Lecture 1: How to become Gen AI Solution Architect

Lecture 2: Developing roadmap for implementing Generative AI Solution