CF

Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4

13h 4m 58s
English
Free

Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4 is a 111-lesson 13 hours 4 minutes self-paced course by Udemy. Unleash the Power of AI: Master OpenAI's APIs, including GPT-4, DALL-E, and Whisper in this Comprehensive and Hands-On Course.

Course facts

Lessons
111
Duration
13 hours 4 minutes
Level
All levels
Language
English
Updated
Instructor
Udemy
Price
Free

Unleash the Power of AI: Master OpenAI's APIs, including GPT-4, DALL-E, and Whisper in this Comprehensive and Hands-On Course. This is a brand new course, recorded with 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.

In this comprehensive course, you will:

  • Develop a deep understanding of OpenAI's generative models and their potential applications
  • Master GPT-4 for natural language processing, including text generation, summarization, translation, and more
  • Use GPT-4 to debug code, improve code, and even write code from scratch
  • Generate visually stunning images and artwork using DALL-E based on textual prompts
  • Convert spoken audio into accurate transcriptions and translations with the power of Whisper
  • Use AI Embeddings to distill, index, search, and compare text, unveiling the geometric power for comparing words, paragraphs, and documents

Real-World Projects for Practical Experience:

  • Create a dynamic Q&A Bot using GPT-4
  • Create a visual color palette search engine with GPT-4
  • Write an interactive code reviewing assistant with GPT-4
  • Create an AI-powered Spotify playlist generator
  • Analyze the sentiment of Reddit comments using GPT-4
  • Summarize books of any size into a couple of paragraphs
  • Create your own interactive, infinite Choose Your Own Adventure application with DALL-E and GPT-4
  • Generate an Emedding-Powered movie recommendation algorithm

Throughout the course, you will engage in hands-on projects and real-world examples, allowing you to immediately apply your newly-acquired knowledge and skills. We also delve into:

  • Best practices for prompt engineering, tokenization, and temperature settings
  • Strategies for optimizing API performance, error handling, and resource management
  • The ethical considerations and challenges associated with AI-driven development

Whether you're a software developer, data scientist, or an AI enthusiast, this course will equip you with the expertise to integrate OpenAI's APIs into your projects and create innovative AI-powered solutions.

Embark on your AI journey and transform your skills with this comprehensive and engaging course. Enroll today and start unlocking the limitless potential of OpenAI's GPT-4, DALL-E, and Whisper APIs!

Who teaches Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4? Udemy

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Udemy is the largest open marketplace for online courses on the internet. Founded in 2010 by Eren Bali, Oktay Caglar, and Gagan Biyani and headquartered in San Francisco, the company went public on the Nasdaq in 2021 under the ticker UDMY. The platform hosts well over two hundred thousand courses across software development, IT and cloud, data science, design, business, marketing, and creative skills, taught by tens of thousands of independent instructors. Roughly seventy million learners use it worldwide, and the corporate arm — Udemy Business — supplies a curated subset of that catalog to enterprise customers.

Because Udemy is a marketplace rather than a single editorial publisher, the catalog is uneven by design. The strongest material lives in the long-form, project-based courses authored by working engineers — full-stack JavaScript, React, Node.js, Python data science, AWS, Docker and Kubernetes, mobile development with Flutter and React Native, and cloud certification preparation. The CourseFlix listing under this source is the slice of that catalog that has been mirrored here for offline-friendly viewing, organized by topic and updated as new releases land. Pricing on Udemy itself swings dramatically with the site's near-permanent sales, which is why the platform is best treated as a deep reference catalog: pick instructors with strong reviews and a track record of updating their material rather than buying on the headline price alone.

What lessons are included in Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4?

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0:00 0:00
#Lesson TitleDuration
1Welcome & Course Overview 11:03
2A Brief History of OpenAI 05:58
3Let's Talk About GPT 06:33
4OPTIONAL: The Transformer Architecture 11:25
5Signing Up For An Account 03:48
6Getting The Course Code 00:40
7Our First Completion Request 08:07
8Hiding Our API Key 06:08
9Understanding Tokens 03:08
10max_tokens 06:21
11Stop Sequences 10:09
12N and Echo 09:27
13The Different Completion Models 10:10
14Comparing Model Performance and Pricing 05:37
15The Elements of a Good Prompt 10:36
16Controlling The Output Format 07:34
17Summarization Prompts 03:34
18Data Extraction Prompts 03:06
19Sentiment Analysis Prompts 03:27
20Zero-Shot Vs. Few-Shot Prompting 04:47
21"Let's Think Step By Step" Prompting 03:31
22Text Transformation Prompts 05:04
23Introducing The Color Palette Project 03:57
24Writing The Color Palette Generator Prompt 08:44
25Writing a Color-Swatch Rendering Function 11:31
26Setting Up The Flask Server 06:03
27Integrating OpenAI With Server 08:14
28Writing the Palette Endpoint 08:43
29Creating The Form 09:46
30Rending The Colors In The Browser 06:24
31Copy and Paste Functionality 06:21
32Styling The Color Blocks 06:42
33Styling The Form 07:14
34Refactoring Our Front-End Code 07:04
35Temperature 11:51
36Understanding Top P 09:07
37Frequency Penalty 10:03
38Presence Penalty 04:54
39Streaming Responses 06:35
40Introducing The Chat API 03:37
41Our First Chat Request 05:56
42Important Note On Pricing! 02:13
43Prompting With Properly Formatted Messages 08:18
44Note on GPT-3.5-Turbo Versions 01:45
45Rewriting a Completion Prompt In Chat Format 08:26
46Chat API Parameters 05:07
47Introducing Our Chatbot Project 02:29
48Writing The Basic Chatbot Structure 07:53
49Persisting Messages Across Requests 08:46
50Adding Optional Personalities 09:21
51Colorizing The Chatbot Output 05:29
52Asking GPT-4 To Explain Code 06:08
53Calculating Time Complexity With GPT-4 07:10
54Translating JS To Python With GPT-4 06:12
55Fixing Code Bugs With GPT-4 06:30
56Generating Code From Scratch With GPT-4 06:17
57Counting Tokens With TikToken 09:10
58Counting GPT-4 Message Tokens 07:10
59Introducing The Basic Code Reviewer 04:08
60Building The Basic Code Reviewer Pt 1 08:26
61Building The Basic Code Reviewer Pt 2 10:21
62Introducing The Interactive Code Reviewer 07:45
63Interactive Code Reviewer Prompt 13:00
64Interactive Code Reviewer Walkthrough 12:04
65Introducing The Spotify Project 04:40
66Writing The Playlist Generating Prompt 12:11
67Finishing The Playlist Prompt 05:38
68Getting Spotify Developer Credentials 03:39
69Spotify Authentication Via Python 07:31
70Searching For Spotify Tracks Via Python 05:33
71Creating Spotify Playlists Programmatically 04:52
72Adding in OpenAI 06:46
73Accepting Command Line Arguments 06:26
74Overview of the Polished Solution 05:21
75Introducing Embeddings 02:39
76Generating a Single Embedding 03:50
77Introducing The Movie Embedding Visualization 04:20
78Getting Our Movie Data Ready 04:39
79Generating Embeddings for 5000 Movies 12:08
80Visualizing Our Embeddings With Atlas 09:34
81Recommending Movies Using Our Embeddings 16:12
82Expanding GPT-4 "Knowledge" With Embeddings 08:03
83Gathering Our Embeddings 11:36
84Implementing Q&A With Embeddings & GPT-4 09:08
85Introducing The Reddit Sentiment Analysis Project 04:59
86Collecting Comments From Reddit 10:10
87Analyzing Sentiment In The Comments 11:49
88Plotting The Results 05:57
89Introducing The Book Summarizer 07:24
90Preparing Book Text For Summarization 07:16
91Context Window Math 08:35
92Summarization Logic 13:44
93Caching Results 04:55
94Performing a "Meta-Summary" With GPT-4 07:56
95Intro To DALL-E 03:46
96Making a DALL-E Request 08:04
97Saving DALL-E Images 12:50
98Alternative Approach To Saving Images 07:38
99Requesting Image Variations 08:24
100DALL-E Image Edits 05:09
101Introducing Stability.AI and Stable Diffusion 04:56
102Using the Stability SDK 07:57
103Introducing The Choose Your Own Adventure Project 05:34
104GPT-4 CYOA Text Generation 09:58
105Stable Diffusion CYOA Image Generation 09:06
106Introducing Whisper 01:58
107The Basics of Whisper 06:30
108Providing a Prompt to Whisper 02:48
109Translating Audio With Whisper 04:52
110Transcribing Non-English Audio 05:01
111Running The Whisper Model Locally 05:49

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Frequently asked questions

What are the prerequisites for this course?
This course is designed for learners of all backgrounds and skill levels. While prior experience with Python or general programming can be helpful, it is not a strict requirement. The course starts with foundational topics such as signing up for an OpenAI account and understanding API keys, making it accessible to beginners interested in AI-driven development.
What projects will I build during the course?
Throughout the course, you will engage in various projects that apply OpenAI's APIs. Notably, you will build a Color Palette Generator using the OpenAI Completion API and a Chatbot using the Chat API. These projects will involve setting up a Flask server, integrating OpenAI with the server, and creating functionalities like rendering color swatches and adding chatbot personalities.
Who is the target audience for this course?
The course is intended for anyone interested in artificial intelligence and AI-driven development, ranging from beginners to those with some programming experience. It provides a comprehensive introduction to using OpenAI's APIs, making it suitable for learners who want to create applications using GPT-4, DALL-E, and Whisper.
How does this course compare in depth and scope to other AI courses?
This course offers a project-driven approach to mastering OpenAI's APIs, focusing on practical applications like building a chatbot and a color palette generator. It covers a wide range of topics, from understanding tokens and model performance to specific prompt engineering techniques. The course's hands-on nature distinguishes it from more theory-focused AI courses.
What specific tools or platforms will I learn to use?
You will learn to use OpenAI's APIs, including GPT-4, DALL-E, and Whisper. The course also involves setting up a Flask server for integrating OpenAI functionalities, using TikToken for counting tokens, and employing various prompt engineering techniques to control and refine AI output.
What topics are not covered in this course?
The course does not cover advanced topics such as neural network architecture design, training custom AI models, or deep learning frameworks like TensorFlow or PyTorch. It focuses on utilizing pre-trained models and APIs rather than developing AI models from scratch.
How much time should I expect to commit to this course?
The course consists of 111 lessons and is designed to be immersive and hands-on. While the total runtime is not specified, students should anticipate a significant time commitment to engage with the projects and fully understand the range of topics covered, including prompt engineering, server integration, and OpenAI API usage.