Master Python OpenAI API & GPT-4: A Project-Based Approach
Master Python OpenAI API & GPT-4: A Project-Based Approach, available at $84.99, with 74 lectures.
You will learn about Learn the fundamentals of the OpenAI Python API and how the API works. Build real-world projects, including a translator, your own chatbot, and an interactive code reviewer. Learn how to work with the latest GPT-4 Model. Learn to Generate, Edit, and Interpret Images using DALL-E 2 & 3. Learn Prompt Engineering to Maximize Responses and Create Quality Output. Generate Voices, Translate Speeches, Text-to-Speech, Speech-to-Text, and More This course is ideal for individuals who are This course is ideal for anyone interested in AI and machine learning, especially those looking to apply AI technologies in practical, impactful ways. Whether you’re an aspiring developer, a seasoned professional, or a curious enthusiast, this course will equip you with the tools and knowledge to excel. It is particularly useful for This course is ideal for anyone interested in AI and machine learning, especially those looking to apply AI technologies in practical, impactful ways. Whether you’re an aspiring developer, a seasoned professional, or a curious enthusiast, this course will equip you with the tools and knowledge to excel.
Enroll now: Master Python OpenAI API & GPT-4: A Project-Based Approach
Summary
Title: Master Python OpenAI API & GPT-4: A Project-Based Approach
Price: $84.99
Number of Lectures: 74
Number of Published Lectures: 74
Number of Curriculum Items: 74
Number of Published Curriculum Objects: 74
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn the fundamentals of the OpenAI Python API and how the API works.
- Build real-world projects, including a translator, your own chatbot, and an interactive code reviewer.
- Learn how to work with the latest GPT-4 Model.
- Learn to Generate, Edit, and Interpret Images using DALL-E 2 & 3.
- Learn Prompt Engineering to Maximize Responses and Create Quality Output.
- Generate Voices, Translate Speeches, Text-to-Speech, Speech-to-Text, and More
Who Should Attend
- This course is ideal for anyone interested in AI and machine learning, especially those looking to apply AI technologies in practical, impactful ways. Whether you’re an aspiring developer, a seasoned professional, or a curious enthusiast, this course will equip you with the tools and knowledge to excel.
Target Audiences
- This course is ideal for anyone interested in AI and machine learning, especially those looking to apply AI technologies in practical, impactful ways. Whether you’re an aspiring developer, a seasoned professional, or a curious enthusiast, this course will equip you with the tools and knowledge to excel.
Artificial Intelligence is rapidly transforming the tech landscape, and mastering it has never been more crucial. In this comprehensive guide, I will teach you how to unleash the power of the OpenAI Python API, using the latest tools and models that AI has to offer.
Unlike many resources on the internet that rely on outdated versions of the OpenAI API, this course was recorded with the latest updates, including GPT-4, GPT-3.5, DALL-E 3, and the newest Whisper and Embeddings models. You’ll gain hands-on experience with cutting-edge AI technologies and learn how to apply them in real-world scenarios.
What You Will Learn
In this course, you will:
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Develop a foundational understanding of how OpenAI operates, its models, and the API’s architecture.
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Learn to use GPT-4 to automate tasks, debug code, refactor code, generate new code from scratch, and even calculate time complexity for projects.
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Explore the DALL-E 3 model and learn how to create beautiful, AI-generated images from textual prompts.
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Use embeddings to compare articles, research documents, or build a recommendation system based on textual queries.
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Convert speeches and audio files into accurate transcriptions and translations, and generate speeches from textual prompts using the latest AI technologies.
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Learn the art and science of crafting focused and powerful prompts that yield the best AI-driven results.
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Deepen your understanding of essential AI concepts, including tokens, language models, and the transformer architecture.
Project-Based Learning
To ensure you truly understand how to work with the OpenAI API, this course is project-based, guiding you through the creation of several exciting and practical projects:
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Build a web-based translator that accurately converts text between languages using the latest AI models.
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Develop your own chatbot using GPT-4.
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Create an AI-powered code reviewer using GPT-4 that can analyze, improve, and even write code for you.
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Design a system that can sift through documents, extract key information, and assist in research tasks.
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Build a recommendation system that tailors suggestions to users based on their preferences.
Who Should Take This Course?
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.
Why Choose This Course?
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Up-to-Date Content: You’ll be working with the latest versions of OpenAI’s tools, ensuring your skills are relevant and cutting-edge.
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Step-by-Step Guidance: No prior AI experience is required each topic is broken down into clear, manageable steps that anyone can follow.
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Risk-Free Learning: This course comes with a 30-day money-back guarantee. If you’re not completely satisfied, you can get a full refund, no questions asked.
Join this course today and start your journey into the world of AI with confidence. By the end, you’ll have not only a deep understanding of the OpenAI Python API but also a portfolio of projects that showcase your ability to apply AI in innovative and impactful ways.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Course outline
Lecture 2: What is OpenAI?
Lecture 3: Environment setup (macOS)
Lecture 4: Environment Overview
Lecture 5: Download: Course materials
Chapter 2: Getting Started
Lecture 1: Getting started with the OpenAI API
Lecture 2: Creating a new API Key
Lecture 3: Important Note: Pricing
Lecture 4: Your first API request
Lecture 5: Diving into the documentation
Lecture 6: Introducing Models
Lecture 7: The pricing system
Lecture 8: What are Tokens?
Lecture 9: Controlling the amount of tokens used (max_tokens)
Lecture 10: Controlling the amount of choices (n)
Lecture 11: Best Practice: Hiding your API Key
Chapter 3: [Project] Creating a Web-Based Translator
Lecture 1: Introducing the Project
Lecture 2: Building the general structure using Flask
Lecture 3: Implementing the OpenAI API
Lecture 4: Make some optional quality changes
Chapter 4: Prompt Engineering
Lecture 1: What is Prompt Engineering & Why it's important
Lecture 2: Transformer Architecture
Lecture 3: Environment setup
Lecture 4: "bad" vs. "good" Prompt
Lecture 5: Key Concepts for a good Prompt
Lecture 6: Crafting effective Prompts
Lecture 7: few-shot and zero-shot (1)
Lecture 8: few-shot and zero-shot (2)
Lecture 9: role-playing and persona-based Prompts
Lecture 10: Analysing data
Lecture 11: Manipulating tone, style and format
Lecture 12: Common Prompt Engineering Pitfalls
Chapter 5: Introducing GPT-4
Lecture 1: Introducing GPT-4
Lecture 2: GPT-4 Pricing
Lecture 3: Working with GPT-4
Chapter 6: [Project] Build your own Chatbot using GPT-4
Lecture 1: Introducing the Project
Lecture 2: Building the basic bot structure (1)
Lecture 3: Building the basic bot structure (2)
Lecture 4: Adding colors
Lecture 5: Adding additional option
Lecture 6: Add Context to the bot
Chapter 7: Working with GPT-4 and Code
Lecture 1: GPT-4 for developers
Lecture 2: Writing code from scratch
Lecture 3: Receive code explanations (existing & generated)
Lecture 4: Debugging your code
Lecture 5: Review your code
Lecture 6: Transform your code
Lecture 7: Plan your project
Chapter 8: [Project] Interactive Code Reviewer
Lecture 1: Introducing the Project
Lecture 2: Building the basic bot structure
Lecture 3: Storing the review in a file
Lecture 4: Making the bot interactive
Lecture 5: Adding colors
Chapter 9: Additional API Request Parameters & Tools
Lecture 1: Define stop sequences (stop)
Lecture 2: Determine the quality of your response (temperature)
Lecture 3: Control the diversity of your response (top_p)
Lecture 4: Calculate your Tokens with Tiktoken
Chapter 10: Embeddings
Lecture 1: What are Embeddings?
Lecture 2: Creating Embeddings
Lecture 3: Example 1: Document Search
Lecture 4: Example 2: Recommendation System
Chapter 11: Working with Audio
Lecture 1: Introducing Text to Speech
Lecture 2: Audio quality & different Voice options
Lecture 3: Supported output formats & languages
Lecture 4: Introducing Speech to Text
Lecture 5: Supported languages
Lecture 6: Translating speeches
Chapter 12: Generating, Edit & Work with Images (DALL-E)
Lecture 1: What is DALL-E?
Lecture 2: Generating your first Image
Lecture 3: Using Prompt Engineering for better output
Lecture 4: Editing your Image
Lecture 5: Image variations
Chapter 13: Course Wrap-Up and Future Opportunities
Lecture 1: Summarizing what you've learned
Lecture 2: What are the next steps?
Instructors
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Pascal Krause
IT Consultant, Software Engineer and passionate Instructor
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