Mastering Python With OpenAI APIs and GPT-4

Mastering Python With OpenAI APIs and GPT-4

Step into the world of artificial intelligence and discover how to harness OpenAI’s cutting-edge APIs, including GPT3, GPT-3.5, GPT4, DALL-E, and Whisper, to create groundbreaking applications and solutions. This immersive, project-driven course is designed for learners of all backgrounds and skill levels, providing a solid foundation in AI-driven development.

What you’ll learn

• Master OpenAI’s GPT-4 and its text completion capabilities
• Understand GPT parameters to fine-tune the model’s performance
• Write, analyze, and debug code in any language using GPT-4
• Structure and refine GPT’s output for consistency and clarity
• Customize GPT-4 to address specific use cases and unique requirements
• Generate and edit images using DALL-E 2
• Employ text embeddings for searching, classifying, and understanding text
• Build an embedding-powered recommendation algorithm
• Use Whisper to translate and transcribe audio files

Course Content:

Module1: Introduction

• Getting Access To Our Discord Community
• A Brief History of OpenAI
• Let’s Talk About GPT
• OPTIONAL: The Transformer Architecture
• Signing Up For An Account03:47
• Getting The Course Code
• Getting The Course Slides

Module2: Getting Started

• Install Requirements
• Our First Completion Request
• For Windows Users: Editing Text Files
• Hiding Our API Key
• Understanding Tokens
• Maxtokens
• Stop Sequences
• N and Echo
• The Different Completion Models
• Comparing Model Performance and Pricing

Module3: Prompt Engineering

• The Elements of a Good Prompt
• Controlling The Output Format
• Summarization Prompts
• Data Extraction Prompts
• Sentiment Analysis Prompt
• Zero-Shot Vs. Few-Shot Prompting
• “Let’s Think Step By Step” Prompting
• Text Transformation Prompts

Module4: Color Palette Generator Project

• Introducing The Color Palette Project
• Color Rendering in Colaboratory
• Writing The Color Palette Generator Prompt
• Writing a Color-Swatch Rendering Function
• Setting Up The Flask Server
• Integrating OpenAI With Server
• Writing the Palette Endpoint
• Creating The Form
• Rending The Colors In The Browse
• Copy and Paste Functionality
• Styling The Color Block
• Styling The Form
• Refactoring Our Front-End Code

Module5: Important API Parameters

• Temperature
• Understanding Top P
• Frequency Penalty
• Presence Penalty
• Streaming Responses

Module6: The Chat API & GPT4

• Introduction to Chat API
• Our First Chat Request
• Important Note On Pricing!
• Prompting With Properly Formatted Messages
• Note on GPT-3.5-Turbo Version
• Rewriting a Completion Prompt In Chat Format
• Chat API Parameters

Module7: Building A GPT-4 Chatbot

• Introducing Our Chatbot Project
• Writing The Basic Chatbot Structure
• Persisting Messages Across Requests
• Adding Optional Personalities
• Colorizing The Chatbot Output

Module8: Working with GPT-4and Code

• Asking GPT-4 To Explain Code
• Calculating Time Complexity With GPT-4
• Translating JS To Python With GPT-4
• Fixing Code Bugs With GPT-4
• Generating Code From Scratch With GPT-4

Module9: Cost Estimation with TikToken

• Counting Tokens With TikToken
• Counting GPT-4 Message Token

Module 10: GPT4 -Automatic Code Review

• Introducing The Basic Code Reviewe
• Building The Basic Code Reviewer Pt 1
• Building The Basic Code Reviewer Pt 2
• Introducing The Interactive Code Reviewer
• Interactive Code Reviewer Prompt
• Interactive Code Reviewer Walkthrough

Module11: GPT-4 AI Spotify Playlist Generator Project

• Introducing The Spotify Project
• Writing The Playlist Generating Prompt
• Finishing The Playlist Prompt
• Getting Spotify Developer Credentials
• Spotify Authentication Via Pytho
• Searching For Spotify Tracks Via Pytho
• Creating Spotify Playlists Programmatically
• Adding in OpenAI
• Accepting Command Line Arguments
• Overview of the Polished Solution

Modue12: Embeddings

• Requirements
• Introducing Embeddings
• Generating a Single Embedding
• Introducing The Movie Embedding Visualization
• Getting our Movie Data
• Getting Our Movie Data Ready
• Generating Embeddings for 5000 Movies
• Visualizing Our Embeddings With Atlas
• Recommending Movies Using Our Embedding

Module13:Using Embedding to Enhance GPT-4

• Expanding GPT-4 “Knowledge” With Embeddings
• Gathering Our Embeddings
• Implementing Q&A With Embeddings & GPT-4

Module14: Sentiment Analysis Project

• Introducing The Reddit Sentiment Analysis Project
• Collecting Comments From Reddit
• Analyzing Sentiment In The Comments
• Plotting The Results

Module15: Book Summarize Project

• Introducing The Book Summarizer
• Preparing Book Text For Summarization
• Context Window Math
• Summarization Logic
• Caching Results
• Performing a “Meta-Summary” With GPT-4

Module16: DALL-E-APP

• Intro To DALL-E
• Making a DALL-E Request
• Saving DALL-E Images
• Alternative Approach To Saving Images
• Requesting Image Variation
• DALL-E Image Edits

Module17: Stable Diffusion

• Introducing Stability.AI and Stable Diffusion
• Using the Stability SDK
• Introducing The Choose Your Own Adventure Project05:33
• GPT-4 CYOA Text Generation
• Stable Diffusion CYOA Image Generation

Module18: Whisper Audio to Text

• Introducing Whisper
• The Basics of Whisper
• Providing a Prompt to Whisper
• Translating Audio With Whisper
• Transcribing Non-English Audio
• Running The Whisper Model Locally

Requirements

• Just some beginner Python experience. That’s it!

Who this course is for

• Developers curious about AI
• Software engineers looking to supercharge their workflow with generative models
• Entrepreneurs interested in the OpenAI’s tools offers
• Content Creators interested in supplementing their creative workflow

Flexible Class Options

• Week End Classes For Professionals  SAT | SUN
• Corporate Group Trainings Available
• Online Classes – Live Virtual Class (L.V.C), Online Training

Flexible Classes Schedule

Online Classes for out of city / country students

Unlimited Learning – FREE Workshops