OpenAI Fundamentals


Course Overview

AI is all around us, and it is no longer just the work of scientists. The OpenAI Fundamentals course is a comprehensive introduction to the concepts and applications of artificial intelligence. In this course, you will learn about the history and evolution of AI, the main branches and techniques of AI, and the current and future challenges and opportunities of AI. By the end of this course, you will have a solid foundation of AI knowledge and skills that will enable you to pursue further learning or career opportunities in this exciting and rapidly growing field.


Key Learning Areas

  • Introduction to AI
  • Introduction to OpenAI
  • Text Completion
  • Code Completion
  • Image Generation
  • Fine-Tuning the OpenAI Model
  • Embeddings OpenAI
  • Limitations and Risks
  • OpenAI API Moderation
  • API Rate Limits
  • Safety Best Practices
  • Production Best Practices

Course Outline

Introduction to AI

  • What is AI?
  • Current State of AI
  • Types of AI
    • Generative AI
  • What is Responsible and trusted AI?
  • Popular AI Tools
  • Large language models
  • Artificial Intelligence: An Overview
  • History of AI
  • AI Today
  • AI Research Areas
  • AI and National Strategies
  • Ethics of Artificial Intelligence
  • What is AI? Applications and Examples of AI
  • AI Concepts, Terminology, and Application Areas
  • Artificial Intelligence and legal issues
  • Technologies and platforms for Artificial Intelligence
  • Machine Learning: an overview

Introduction to OpenAI

  • What is OpenAI?
  • Start with an Instruction
  • Add Examples
  • Adjust Settings
  • Build Application
  • Libraries
  • Models
  • Usage Policies

Text Completion

  • Introduction
  • Prompt Design
  • Inserting Text
  • Editing Text

Code Completion

  • Introduction
  • Best Practices
  • Inserting Code
  • Editing Code

Image Generation

  • Usage
  • Language-Specific Tips

Fine-Tuning OpenAI Model

  • Preparing Dataset
  • Advanced Usage
  • Weights and Biases

Embeddings Open AI

  • What are Embeddings?
  • How to Get Embeddings?
  • Embedding Models
  • Use Cases

Limitations and Risks

Open AI API Moderation

  • Overview
  • Quickstart

API Rate Limits

  • What are Rate Limits?
  • Why Do We Have Rate Limits?
  • Rate Limits of Our API
  • How do Rate Limits Work?
  • Rate Limit Errors
  • Error Mitigation
  • Request Increase

Safety Best Practices

  • Use Moderation API
  • Adversarial Testing
  • Human in the Loop (HITL)
  • Prompt Engineering
  • Know Your Customer (KYC)
  • Constrain User Input and Limit Output Tokens
  • Allow Users to Report Issues
  • Understand and Communicate Limitations
  • End-User IDs

Production Best Practices

  • Setting Up Your Organization
  • Building Your Prototype
  • Evaluation and Iteration
  • Scaling Your Solution
  • Managing Rate Limits
  • Improving Latencies
  • Managing Costs
  • MLOps Strategy
  • Security and Compliance

Who Benefits

Anyone who understands the basic concept of cloud, internet, data, ML, and app development.



Want this course for your team?

Atmosera can provide this course virtually or on-site. Please reach out to discuss your requirements.