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AI

Introduction to OpenAI

Unlock the power of AI with the Introduction to OpenAI Course—your hands-on guide to mastering advanced language and vision models for real-world, transformative applications!
Gav Ridegeway
Devops Expert, Machine Learning Engineer
DevOps Pre-Requisite Course
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What you’ll learn

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Description

Welcome to the Introduction to OpenAI Course, a gateway into the world of artificial intelligence and advanced language models! In today’s fast-paced AI environment, understanding the foundational elements of AI is essential. But the true value lies in knowing how to effectively use OpenAI’s tools and frameworks to create meaningful, transformative AI applications. If you’ve ever felt uncertain about working with complex AI models, you're in the right place. While introductory tutorials often provide a basic overview, this course goes further—guiding you through real-world OpenAI applications with depth and clarity.

This course is designed for learners who are ready to bridge the gap between theoretical AI concepts and practical implementations using OpenAI’s platform. Through hands-on, scenario-based lessons, you’ll build the skills to confidently work with OpenAI tools, advancing beyond the basics to gain valuable, applicable insights into AI modeling.

Course Modules:

  1. Pre-requisites
    Begin your journey with essential foundational steps, including an introduction to OpenAI, account setup, and an overview of OpenAI’s platform. You’ll also learn about securing API keys, understanding OpenAI’s model options, and navigating key libraries and changelogs. These prerequisites ensure you have a strong start and essential tools for success.
  2. Introduction to AI
    Dive into the evolution of AI from rule-based systems to deep learning, and discover how transformers and attention mechanisms power today’s generative AI models. This module covers vital topics like prompt engineering, tokenization, and pre-training, offering labs and practical exercises to deepen your understanding. You’ll also explore AI ethics, multimodal inputs, and reinforcement learning—key considerations for responsible and effective AI solutions.
  3. Text Generation
    Learn the ins and outs of text generation, from prompt engineering to practical applications. Hands-on labs and projects will guide you through creating text-based solutions like recipe generators, article translators, and short story generators. You’ll delve into OpenAI’s tools for sentiment analysis, fine-tuning, text-to-speech, and embeddings, and create projects such as an AI research assistant and a personalized AI trainer. This module brings the power of text generation into real-world scenarios.
  4. Features
    Gain expertise in structured outputs, function calling, and batch processing with OpenAI. This module also covers advanced usage techniques, including content moderation. Through labs, you’ll explore practical applications, ensuring you can manage and scale AI solutions effectively.
  5. Vision
    Discover OpenAI’s cutting-edge vision capabilities with DALL-E and CLIP. This module provides an overview of DALL-E's text-to-image generation, evolution, and applications across industries. You’ll undertake projects like image generation and captioning, learn fine-tuning techniques, and discuss ethical considerations. As you complete this module, you'll gain insight into current limitations, future innovations, and the transformative potential of AI-driven vision technologies.

Through this hands-on, project-based course, you’ll develop a robust understanding of OpenAI’s language and vision models, enabling you to build innovative applications. Whether you're aiming to deepen your knowledge of AI or apply it to real-world challenges, this course equips you with the tools to excel in OpenAI’s ecosystem and beyond.

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What our students say

About the instructor

Gav Ridgeway is a self-taught developer with many years of experience in Python, Data Science, Machine Learning, Artificial Intelligence, and Game Development. As a self-taught developer, Gav understands what it takes to learn and teach new and complex topics. He brings this unique perspective to all his courses. His skills encompass various tools & libraries such as: Pandas, NumPy, PyTorch, Linear Regression, NLP, SVM’s and much more.

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Pre-Requisites

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Lesson Content

Module Content

Introduction to Course 02:33
Introduction to OpenAI 03:08
History of OpenAI 01:35
How OpenAI Works​ 04:31
Why We Need OpenAI​ 05:29
Benefits of OpenAI for Industries​ 05:22
OpenAI Account Setup 03:37
Getting Started With OpenAI Platform 04:15
What Are API Keys and How to Protect Them 02:33
Understanding OpenAI Models 10:19
OpenAI Libraries 05:28
OpenAI Changelogs 04:41

Introduction to AI

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Module Content

The Evolution of AI: From Rule-Based Systems to Deep Learning 12:49
Transformers and How They Power Generative AI 12:24
Understanding Attention Mechanisms in Transformers 08:22
The Role of Pre-Training and Fine-Tuning in LLMs 08:30
Basic Prompt Engineering 12:39
Lab: Basic Prompt Engineering
Tokenization and Its Impact on AI Models 08:21
Zero-Shot and Few-Shot Prompting 08:06
Grounding LLMs for Increased Accuracy 07:51
How Encoders Allow LLMs to Process Prompts 09:24
Exploring Bias and Fairness in Language Models 06:56
Integrating Multimodal Inputs in Generative AI 07:31
Reinforcement Learning in AI Systems 10:22
Ethical Considerations in Generative AI 09:09

Text Generation

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Overview of Text Generation 16:08
Prompt Engineering 06:47
Practical Applications 02:32
Chat Completions 05:27
How to Generate API Key Securely 02:57
Lab: Generating API and Securing It
Project 1: Recipe Generator 10:10
Project 2: Translating an Article 06:20
Lab: Creating Your Own Short Story Generator
Sentiment Analysis With OpenAI 06:24
Overview of OpenAI Assistant 05:40
Creating an Assistant - Part 1 02:17
Creating an Assistant - Part 2 07:01
Project 3: AI Research Assistant 07:01
Project 4: Personal Trainer 09:06
Fine-Tuning 06:35
Embeddings 08:14
Embeddings Demo 02:56
Text to Speech 08:54
Speech to Text 03:04
Lab: Text to Speech

Features

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Module Content

Structured Outputs 05:09
Function Calling: Structured Outputs 04:40
Advanced Usage 05:07
Batch Processing 06:56
Lab: Batch Processing
Moderation 05:25

Vision

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Overview of OpenAI Vision 08:22
DALL-E: What It Is and How It Works 04:11
The Evolution of DALL-E: From DALL-E 1 to DALL-E 3 05:24
Understanding DALL-E Text-to-Image Generation 05:30
Practical Applications of DALL-E in Various Industries 06:43
Introduction to Contrastive Language-Image Pretraining (CLIP) 04:15
Project 1: Image Generator 05:38
Project 2: Image Captioning 05:49
Lab: Creating Your Own Images
Fine-Tuning 03:26
Practical Vision Applications 04:45
Limitations, Challenges, and Ethical Considerations 04:59
Future Trends and Innovations in OpenAI Vision 03:20
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