Openai Api Mastery: From Beginner To Expert

Openai Api Mastery: From Beginner To Expert
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 2.98 GB[/center]
| Duration: 6h 23m
Build OpenAI Apps with Python & Streamlit. Explore Chat Completion, Assistant API & Fine-Tuning, GPT 3.5, GPT 4

What you'll learn

Fine-tuning OpenAI models for specific tasks and applications

Create Assistant API app with Streamlit

Harness the power of the Assistant API in Python for intelligent interactions

Create a ChatGPT app using Streamlit for interactive chat experiences

Dive into building chat completion applications using Python

Get introduced to the OpenAI API and its capabilities

Implement OpenAI API functionalities in Python for various applications

Explore the OpenAI Playground, including the Completion API, Chat Completion, and Assistant features

Gain an understanding of Large Language Models and their significance in modern AI applications

Learn basic prompt engineering techniques to effectively interact with OpenAI models

Requirements

Basic understanding of Python programming language. Familiarity with concepts such as variables, loops, and functions

Access to a computer with internet connectivity

Eagerness to learn and explore the possibilities of OpenAI technology

Description

Welcome to the comprehensive course on OpenAI API Mastery: From Beginner to Expert In this course, we'll embark on an exciting journey to explore the capabilities of one of the most powerful AI technologies available today. Whether you're a beginner in Python or an experienced developer looking to enhance your skills in natural language processing and AI application development, this course is designed to equip you with the knowledge and skills needed to build intelligent applications using the OpenAI API.We'll start by laying the foundation with an introduction to Large Language ModelsUnderstanding their significance in the realm of artificial intelligence. From there, we'll delve into the basics of prompt engineering techniques, essential for effectively interacting with OpenAI models. You'll then be introduced to the OpenAI API, gaining insights into its functionalities and capabilities.Next, we'll dive into the OpenAI Playground, where we'll explore key features such as the Completion APIChat Completion,Assistant APIKnowledge RetrievalCode InterpreterFunction Calling functionalities. Through hands-on exercises and projects, you'll learn how to leverage these features to build intelligent chat applications and interactive assistants.Moving forward, we'll explore how to implement the OpenAI API in Python, enabling you to harness the power of AI within your own applications. We'll specifically focus on the chat completion API, teaching you how to integrate it into Python applications and build a ChatGPT app using Streamlit for a seamless user experience.But we won't stop there. We'll also cover the Assistant API, demonstrating how to use it to create intelligent assistants capable of assisting users with various tasks and inquiries. Additionally, you'll learn how to build a Data Visualizer app using the Assistant API in Python with StreamlitEnhancing data understanding and analysis with Assistant APIFinally, we'll delve into the process of fine-tuning OpenAI models for specific tasks and applications, allowing you to tailor the models to suit your unique needs. Throughout the course, you'll not only gain practical skills in AI application development but also understand the broader implications of OpenAI technology in today's world.By the end of this course, you'll emerge as a proficient developer capable of harnessing the power of the OpenAI API to build intelligent, innovative, and impactful applications that have the potential to transform industries and enrich lives. So, are you ready to unlock the full potential of AI? Let's get started!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Create OpenAI Account

Section 2: Large Language Models (LLMs) Essential Concepts

Lecture 3 What will you learn

Lecture 4 Foundation of Large Language Models

Section 3: OpenAI Playground - No Coding

Lecture 5 OpenAI API

Lecture 6 Usage/Billing, Settings, Rate Limit

Lecture 7 "Completion"

Lecture 8 "Chat"

Section 4: Assistants in Playground

Lecture 9 "Assistant"

Lecture 10 "Assistant" - Knowlege Retrival

Lecture 11 "Assistant" - Code Interpreter (Analysis data in csv file)

Lecture 12 Data Analysis Assignment with Assistant

Section 5: OpenAI API with Python

Lecture 13 Create API (Secret Keys)

Lecture 14 Setting up Python for OpenAI

Lecture 15 Setting up your Secret key in Python

Lecture 16 Sending API request to OpenAI - part1

Lecture 17 Sending API request to OpenAI - part2

Lecture 18 Sending API request to OpenAI - part3

Lecture 19 Stream API request to OpenAI

Section 6: Create ChatGPT App in Steamlit

Lecture 20 ChatGPT App with OpenAI API - part1 (Chat Elements)

Lecture 21 ChatGPT App with OpenAI API - part2

Lecture 22 ChatGPT App with OpenAI API - part3

Section 7: Assistant API in Python

Lecture 23 What is Assistant API

Lecture 24 How Assistant API works

Lecture 25 Assistant API Playground Logs Review

Lecture 26 Run Lifecycle of Assistant API

Lecture 27 Create Assistants in Python

Lecture 28 Create Thread and Message for Assistant

Lecture 29 Create Run and run the assistant

Lecture 30 Get response for another Prompt (Create Assistant Run Function)

Lecture 31 Visualization with Assistants (Get Plots from Data) part 1

Lecture 32 Visualization with Assistants (Get Plots from Data) part 2

Lecture 33 Create Data visualizer Assistant App in Streamlit

Lecture 34 Data Visualizer Assistant App in Streamlit - part 2 (thread, sesssion state)

Lecture 35 Data Visualizer Assistant App in Streamlit - part 3 (chat_input, chat_message)

Lecture 36 Data Visualizer Assistant App in Streamlit - part 4 (connect to assistants)

Lecture 37 Data Visualizer Assistant App in Streamlit - part 5

Lecture 38 Prompts to get more visualization on data

Section 8: BONUS

Lecture 39 Bonus Lecture

Python enthusiasts eager to delve into the world of AI and natural language processing,Students or professionals looking to enhance their skills in AI development and application building,Entrepreneurs or tech enthusiasts interested in creating innovative AI-powered solutions,Anyone curious about leveraging the potential of OpenAI technology to develop intelligent and interactive applications