Complete OpenAI API Masterclass for Beginners using Python

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Pragmatic Code School

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1 - Getting Started With the Course

1 - Course Introduction.mp4

05:12

2 - Prerequisites.mp4

01:36

2 - Course Slides and Source Code

3 - Course slides.html

3 - openai-chatgpt.zip

4 - Github Source Code.txt

4 - Source Code.html

3 - Introduction to Large Language Models LLMs OpenAI ChatGPT Theory

5 - The World Before LLMs A Glimpse into the Past.mp4

05:33

6 - Large Language Models and its Evolution.mp4

08:27

7 - How are LLMs Models Trained.mp4

04:14

8 - GPT Models and its Evolution.mp4

07:40

9 - Advantages Challenges and Applications using LLMs.mp4

07:03

10 - Sign up for a ChatGPT Account and Start Exploring.mp4

06:34

4 - OpenAI APIs Your First Steps to Mastery

11 - Introduction to OpenAI API.mp4

06:51

11 - Openai platform.txt

12 - OpenAI Platform Playground.txt

12 - Setup OpenAI Account Open AI Playground.mp4

07:17

13 - Setup python in Mac.mp4

05:30

14 - Setup python in Windows.mp4

01:59

15 - 4.2.1-base-project-poetry.zip

15 - Set up the Base Project using Poetry.mp4

07:29

16 - Set up OpenAI APIKey.mp4

03:29

16 - apikeys.txt

16 - env file.txt

17 - 4.4-openai-client.zip

17 - Interact with GPT using OpenAI Client.mp4

13:38

18 - 4.4.1-openai-client.zip

18 - Structuring API Calls with Functions.mp4

04:08

19 - Prompt Tokens and Tokenization What are they.mp4

05:43

19 - Tokenizer.txt

20 - 4.6-openai-client-temperature.zip

20 - Chat API Reference.txt

20 - OpenAI Request Parameters temperature.mp4

08:32

21 - 4.7-openai-client-maxtokens.zip

21 - OpenAI Request Parameters maxtokens.mp4

03:09

21 - Tokenization In OpenAI API Lets Explore Tiktoken Library.txt

21 - Tokenizer.txt

22 - 4.8-openai-client-top-p.py.zip

22 - OpenAI Request Parameters topp.mp4

04:59

23 - 4.9-stream.py.zip

23 - Streaming OpenAI Responses.mp4

06:10

24 - Open AI Playground.txt

24 - Understanding System Assistant and User Messages in OpenAI.mp4

07:05

25 - 4.11-gpt-openai-user-system-message.py.zip

25 - System Assistant and User Messages in Action.mp4

06:11

5 - Mastering Multimodality Creating and Editing Images with OpenAI

26 - Introduction to MultiModality in AI.mp4

02:40

27 - 5.1-create-an-image.zip

27 - Creating an Image using OpenAI.mp4

05:28

28 - 5.2-create-an-image-file.zip

28 - Refactor Code to Write the Image in the file system.mp4

04:29

29 - 5.3-create-variation.py.zip

29 - Create an variation using the createvariation function.mp4

03:49

6 - Mastering Multimodality Exploring Vision Capabilities with OpenAI

30 - Unlocking Vision Image Understanding Capabilities using Image URL.mp4

09:23

31 - Unlocking Vision Understanding Capabilities using Encoded Image.mp4

09:46

32 - Vision API.txt

32 - Vision API Limitations.mp4

01:52

32 - Vision Limitations.txt

7 - Mastering Multimodality Creating and Processing Audio with OpenAI

33 - 7.1-TTS.zip

33 - From Speech to Sound Converting Text to Voice with OpenAIs TTS Model.mp4

10:56

33 - TexttoSpeech.txt

34 - Introduction to the Whisper API in OpenAI.mp4

03:03

34 - SpeechToText.txt

35 - Transcribing Speech using Whisper API in OpenAI.mp4

09:49

36 - Translation using Whisper API in OpenAI Translate from French to English.mp4

04:33

8 - Prompt Engineering

37 - Prompt Engineering PromptTemplate.mp4

04:08

38 - Set up Project for Prompt Engineering.mp4

02:11

39 - Prompt Engineering in Action Lets explore the Travel Plan Prompt.mp4

11:51

40 - Understanding Prompt Injection and How to Mitigate It.mp4

06:03

41 - Zero Shot Prompting.mp4

05:08

42 - Few Shot Prompting.mp4

04:43

43 - Chain of Thought Prompting.mp4

11:52

44 - Mastering MultiStep Prompts.mp4

09:39

9 - Generating Structured Data with OpenAI

45 - Introducing Structured Outputs in the API.txt

45 - Introduction to Structured Outputs in LLM.mp4

07:31

46 - Structured outputs using Prompt Engineering.mp4

07:58

47 - Structured outputs with Few Shot Examples using Prompt Engineering.mp4

08:34

48 - Pydantic in Action.mp4

09:10

49 - Structured outputs with Pydantic Model Validations using Prompt Engineering.mp4

07:45

50 - Structured outputs using responseformat and pydantic.mp4

05:39

10 - Function Calling using tools with OpenAI

51 - Function Calling What Why.mp4

10:43

52 - 10.2-function-calling-system-time.py.zip

52 - Function Calling with OpenAI Accessing System Name and Time.mp4

13:01

53 - 10.3-command-line-app.py.zip

53 - Building an Interactive CommandLine App.mp4

05:27

54 - Connecting OpenAI Function Calling to Open Meteo API for Realtime Weather Data.mp4

12:48

55 - Realtime Stock Price Retrieval using OpenAI Function Calling.mp4

14:03

Description

Master AI App Development using OpenAI API integration, Prompt Engineering, Function Calling and Structured Outputs.

What You'll Learn?

Learn to interact with OpenAI Platform (Generative AI) using Python Code
Learn the LLM basics, ChatGPT evolution, training, and practical usage.
Learn to work and explore the multimodal capabilities such as images, files, audio using OpenAI and Python code.
Learn to use Prompt Engineering to guide AI models in generating accurate outputs.
Learn to use latest techniques to generate the Structured Outputs from LLM
Learn to use the power of function calling with OpenAI to interact with external systems
Build a Chatbot using Streamlit
Explore the features of OpenAI Canvas, A modern collaborative tool for writing code.

Who is this for?

Software Developers looking to integrate AI capabilities into their applications using OpenAI and Python.

Data Scientists interested in enhancing their skill set with AI application development.

AI Enthusiasts who want to explore practical implementations of OpenAI’s APIs and ChatGPT.

Machine Learning Engineers aiming to expand their knowledge by incorporating language models into projects.

Entrepreneurs and Startups aiming to build AI-based products or services quickly and efficiently.

Students and Graduates in computer science or related fields who want hands-on experience with AI applications.

Anyone Curious About AI with a foundational understanding of Python and a desire to learn about AI application development.

What You Need to Know?

Experience with Python

Experience working with IDE such as Visual Studio Code.

More details

Description
"AI Application Development with OpenAI, ChatGPT, and Python" is a comprehensive course designed to teach you how to harness the power of OpenAI's APIs and tools to build advanced AI applications.
You'll explore the fundamentals of Large Language Models (LLMs), understand the evolution of ChatGPT, and gain hands-on experience in using OpenAI's capabilities for text, image, and audio processing.
The course covers essential topics such as prompt engineering, structured data generation, and function calling, enabling you to create dynamic and interactive AI solutions.
Whether you're a developer, data scientist, or AI enthusiast, this course provides the knowledge and skills to develop cutting-edge AI applications using Python and OpenAI.

1. Getting Started with the Course
This section introduces the course, outlining what you can expect to learn and achieve by the end of it. We will cover how to set up your environment, download course materials, and access the resources needed to follow along.
2. Introduction to Large Language Models (LLMs), OpenAI & ChatGPT
Dive into the world of LLMs with an in-depth look at OpenAI's ChatGPT, its architecture, and how itâ€™s revolutionizing AI-driven language processing. Explore the history of how we interacted with computers before LLMs and how it has evolved since the release of ChatGPT. You'll trace the evolution of LLMs and understand the complexities involved in training these models.
3. OpenAI APIs: Your First Steps to Mastery
Master the essential steps for working with OpenAI APIs, from setting up your environment on Mac or Windows to making your first API requests. This section covers everything from installing Python, managing dependencies using Poetry or pip, configuring your OpenAI API key, and interacting with GPT models using OpenAI clients.
4. Mastering Multimodality: Creating and Editing Images with OpenAI
Learn how to leverage OpenAI's capabilities to generate and edit images. This section introduces you to multimodality in AI, combining text and image generation. Youâ€™ll explore how to create images, edit them, and use OpenAI's variation functions to enhance creativity.
5. Mastering Multimodality: Exploring Vision Capabilities with OpenAI
Delve into the vision capabilities of OpenAI. You'll learn how to analyze images using URLs, process base64-encoded images, and understand the limitations of OpenAIâ€™s Vision API. This knowledge will help you integrate vision-based AI solutions into your projects.
6. Mastering Multimodality: Creating and Processing Audio with OpenAI
Explore how OpenAI handles audio data, including text-to-speech conversion, speech-to-text transcription, and language translation using the Whisper API. You will gain hands-on experience in converting written text into speech and transcribing spoken language into text.
7. Prompt Engineering
This section covers the art of crafting prompts to guide AI models in generating accurate outputs. Youâ€™ll learn about various prompting techniques, including zero-shot and few-shot prompting, and how to structure prompts to achieve desired results. Youâ€™ll also explore how to protect prompts from injection attacks.
8. Generating Structured Data with OpenAI
Understand how to generate structured data using OpenAI's LLMs. This section includes prompt engineering techniques, using Pydantic for data validation, and advanced methods for structured outputs. You'll learn how to manage structured data in Python efficiently and how to combine Pydantic with prompt engineering for accurate data generation.
9. Function Calling using Tools with OpenAI
Discover how to use OpenAI for function calling to interact with external systems, retrieve real-time data, and build interactive applications. You'll learn how to connect OpenAI to APIs for real-time data, such as weather updates and stock prices, making your AI applications more dynamic and responsive.
This comprehensive course will equip you with the skills needed to build AI-powered applications using OpenAI's powerful tools and APIs. Join us as we embark on this journey to master the art of AI application development with hands-on projects and real-world examples.

Who this course is for:
Software Developers looking to integrate AI capabilities into their applications using OpenAI and Python.
Data Scientists interested in enhancing their skill set with AI application development.
AI Enthusiasts who want to explore practical implementations of OpenAIâ€™s APIs and ChatGPT.
Machine Learning Engineers aiming to expand their knowledge by incorporating language models into projects.
Entrepreneurs and Startups aiming to build AI-based products or services quickly and efficiently.
Students and Graduates in computer science or related fields who want hands-on experience with AI applications.
Anyone Curious About AI with a foundational understanding of Python and a desire to learn about AI application development.

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