OpenAI API with Python Bootcamp: ChatGPT API, GPT-4, DALL·E

9h 8m 16s
English
Paid

Course description

Welcome to the best resource for learning the OpenAI API with Python and for integrating the latest OpenAI models into your applications.

This OpenAI API with Python Bootcamp covers every model released by OpenAI that has an API, including GPT-3 (DaVinci), ChatGPT (GPT-3.5-TURBO and GPT-4), DALL-E, and Whisper!

By the end of this course, you will have in-depth knowledge and a vast hands-on experience with the OpenAI API, and you will be an expert able to make your Python applications intelligent.

This is a brand new OpenAI API course that will be constantly updated to teach you the skills required for the future.

You will be a pioneer who will be shaping the future of technology and will benefit from the first-mover advantage.

Read more about the course

Projects developed in this course:

Project #1- Zero-Shot Sentiment Analysis Using ChatGPT

Project #2 - Building a ChatGPT Clone From Scratch (ChatBot)

Project #3 - Building a Healthy Daily Meal Plan

Project #4 - Program like a Pro with GPT-4

Project #5 - Boost Your Linux Sysadmin Capabilities with ChatGPT (ShellGPT)

Project #6 - YouTube Videos Summary Generator

Project #7 - Books Recommendation System

Here are two reasons why you should take this course:

1. I took my first Artificial Intelligence course at the Faculty of Mathematics, Statistics, and Informatics back in the early 2000s. I'm not just some random guy who just learned about OpenAI, ChatGPT, or GPT-4 and is now teaching online courses. I have a lot of real-world experience in both teaching and practicing.

2. We'll start from the basics and learn together, step-by-step, side-by-side, line-by-line, how to make API calls from Python to OpenAI models such as GPT-3, ChatGPT, GPT-4, DALL-E, or Whisper. I won't show you how to use the web interface of ChatGPT, but we'll go really deep into how these models work and we'll also develop real-world projects in Python that can be used as templates for your next projects.

You'll have access to my closed and exclusive online group to provide you with improved, faster, and better support for your course-related questions.

You'll have lifetime access and you can return and look for a specific concept or piece of code anytime you want. And don't forget, if you don't like the course, you're covered by a 30-day money-back guarantee, full refund, no questions asked!

The topics covered in this OpenAI API with Python course are:

  • Installing and Working with Jupyter Notebook

  • Creating an OpenAI Account and an API Key

  • Installing the OpenAI API Library and Authenticating to OpenAI

  • OpenAI Models: Davinci, GPT-3.5-TURBO, GPT-4, DALL-E, Whisper

  • Making GPT-3 Requests Using the OpenAI API

  • Making ChatGPT, GPT-3.5-TURBO, and GPT-4 Requests Using the OpenAI API

  • Diving into ChatGPT

  • OpenAI API Costs

  • Tokens

  • OpenAI Model Completion Parameters

  • ChatGPT System Role

  • Prompt Engineering

  • Image Generation Using the DALL-E Model

  • Using DALL-E to Create Variations and Edit Images

  • Diving into DALL-E

  • Speech Recognition With Whisper

  • Text Embeddings (text-embedding-ada-002)

  • Creating web interfaces for your apps using Streamlit

  • Streamlit: main concepts, widgets, session state, callbacks.

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#1: How to Get the Most Out of This Course

All Course Lessons (76)

#Lesson TitleDurationAccess
1
How to Get the Most Out of This Course Demo
02:24
2
Setting Up the Environment: Jupyter Notebook and Google Colab
14:43
3
Creating an OpenAI Account and an API Key
03:57
4
Installing the OpenAI API Library and Authenticating to OpenAI
08:49
5
OpenAI Models
06:52
6
Making GPT-3 Requests Using the OpenAI API
07:31
7
Making ChatGPT Requests Using the OpenAI API
09:01
8
Diving into ChatGPT
07:36
9
Diving into GPT-4
09:22
10
OpenAI API Costs
03:38
11
Tokens
03:59
12
OpenAI Model Completion Parameters
12:33
13
ChatGPT System Role
04:44
14
Prompt Engineering
13:03
15
Image Generation Using the DALL-E Model
11:02
16
Using DALL-E to Create Variations and Edit Images
09:39
17
Diving into DALL-E
03:57
18
Speech Recognition With Whisper
08:12
19
Project Requirements
01:26
20
Building the Application
04:48
21
Testing the Application
08:22
22
Building a Front-End Using Streamlit
05:46
23
Creating the Web App Layout With Streamlit
07:48
24
Saving and Displaying the History Using the Streamlit Session State
05:26
25
Project Requirements
03:43
26
Making a Dialog With the AI Model
10:07
27
Looping
09:57
28
Testing the Project and Python Script Overview
09:33
29
Project Requirements
01:25
30
Creating the Meal Plan Using the ChatGPT API
07:36
31
Generating Meal Images Using DALL-E
10:40
32
YouTube Videos Summary Generator: Project Requirements
05:38
33
Building a YouTube Downloader With Python
13:56
34
The YouTube Download Function
05:45
35
Transcribing Using Whisper
05:29
36
Summarizing Using GPT
06:16
37
Testing the Application and Adding Enhancements
13:46
38
Coding a Simple Application: Password Generator
03:41
39
Coding an Intermediate-level Application with GPT-4: The Tetris Game
05:03
40
Coding a Complex Application with GPT-4: Voice Assistant
13:19
41
Intro to OpenAI's Text Embeddings
03:22
42
Generating Simple Embeddings
06:48
43
Finding Similarities Using Embeddings
13:45
44
Performing Semantic Searches
10:20
45
Project Introduction
03:38
46
Building the Application - Part 1
12:42
47
Building the Application - Part 2
09:52
48
Testing the Application
05:04
49
Visualizing Embeddings
04:57
50
Displaying Embeddings on Atlas
10:42
51
Project Introduction
04:09
52
Installing and Configuring ShellGPT
10:25
53
Using ShellGPT like a PRO
12:25
54
The Chat Feature of ShellGPT
08:14
55
While and continue Statements
04:18
56
While and break Statements
05:48
57
List Slicing and Iteration
07:27
58
List Comprehension - Part 1
06:16
59
List Comprehension - Part 2
06:40
60
Working with Dictionaries
10:40
61
JSON Data Serialization
06:41
62
JSON Data Deserialization
05:50
63
Assignment: JSON and Requests/REST API
02:00
64
Assignment Answer: JSON and Requests/REST API
03:59
65
Introduction to Streamlit
04:52
66
Streamlit Main Concepts
05:52
67
Displaying Data on the Screen: st.write() and Magic
05:49
68
Widgets, Part 1: text_input, number_input, button
05:22
69
Widgets, Part 2: checkbox, radio, select
07:47
70
Widgets, Part 3: slider, file_uploader, camera_input, image
10:39
71
Layout: Sidebar
02:11
72
Layout: Columns
06:01
73
Layout: Expander
02:22
74
Displaying a Progress Bar
04:10
75
Session State
09:22
76
Callbacks
07:15

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