OpenAI API Guide: Make Full Featured AI Applications
OpenAI API Guide: Make Full Featured AI Applications, available at $74.99, has an average rating of 4.3, with 53 lectures, 2 quizzes, based on 52 reviews, and has 1237 subscribers.
You will learn about What is the OpenAI API LLMs, transformers, and high level how they work How to generate text with the OpenAI API How to summarize with OpenAI API How to translate with OpenAI API How to Fine Tune GPT 3.5 Turbo How to use OpenAI API with other libraries Deploying OpenAI applications with GCP and AWS How to use GPT Builder to create custom GPTs This course is ideal for individuals who are Beginner Python users and software engineers that want to develop an AI application with OpenAI API or Entrepreneurs that want to build their own AI application or Software engineers that want to create AI applications It is particularly useful for Beginner Python users and software engineers that want to develop an AI application with OpenAI API or Entrepreneurs that want to build their own AI application or Software engineers that want to create AI applications.
Enroll now: OpenAI API Guide: Make Full Featured AI Applications
Summary
Title: OpenAI API Guide: Make Full Featured AI Applications
Price: $74.99
Average Rating: 4.3
Number of Lectures: 53
Number of Quizzes: 2
Number of Published Lectures: 53
Number of Published Quizzes: 2
Number of Curriculum Items: 55
Number of Published Curriculum Objects: 55
Original Price: $24.99
Quality Status: approved
Status: Live
What You Will Learn
- What is the OpenAI API
- LLMs, transformers, and high level how they work
- How to generate text with the OpenAI API
- How to summarize with OpenAI API
- How to translate with OpenAI API
- How to Fine Tune GPT 3.5 Turbo
- How to use OpenAI API with other libraries
- Deploying OpenAI applications with GCP and AWS
- How to use GPT Builder to create custom GPTs
Who Should Attend
- Beginner Python users and software engineers that want to develop an AI application with OpenAI API
- Entrepreneurs that want to build their own AI application
- Software engineers that want to create AI applications
Target Audiences
- Beginner Python users and software engineers that want to develop an AI application with OpenAI API
- Entrepreneurs that want to build their own AI application
- Software engineers that want to create AI applications
Harness the power of ChatGPT and OpenAI API to perform a variety of language tasks, including summarization, translation, chat completion, and categorization. This comprehensive course will guide you from beginner to expert, empowering you to leverage these cutting-edge tools for real-world applications.
Key Course Takeaways:
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Unravel the Fundamentals of OpenAI API: Delve into the intricacies of OpenAI API, understanding its architecture and mastering its capabilities for text generation.
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Empower ChatGPT with OpenAI API: Seamlessly integrate ChatGPT with OpenAI API, enabling you to seamlessly interact with chatbots and execute code
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Build Projects with ChatGPT, OpenAI API, and Google Cloud APIs: Embark on practical projects that showcase the power of these tools, including:
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Summarization Tool: Automatically condense text documents into concise summaries.
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Translation Tool: Bridge language barriers by translating text seamlessly
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Chat Completion Tool: Enhance chatbot interactions with context-aware responses.
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Categorization Tool: Automate sentiment analysis and classify text effectively
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Food Calorie Counter: Analyze images to estimate food calories accurately.
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Prompt Engineering: Generate captivating phone wallpapers from text descriptions.
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Fine-Tuning GPT 3.5 Turbo Model: Unleash the full potential of GPT 3.5 Turbo Model with OpenAI API.
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RAG (Retrieval Augmented Generation):Learn how AI Applications are architectured and how to use RAG
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Comprehensive Learning Experience:
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Foundations of Transformers: Grasp the core concepts of Transformers, the revolutionary architecture behind ChatGPT.
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OpenAI API Mastery: Develop a thorough understanding of OpenAI API, enabling you to perform complex language tasks with ease.
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Practical Language Processing Applications: Master summarization, translation, chat completion, and categorization using ChatGPT and OpenAI API
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Google Cloud API Integration: Leverage Google Cloud APIs, including Text-to-Speech, GPT4-Vision, and Image Generation, to enhance your projects.
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Prompt Engineering Expertise: Command the art of prompt engineering, controlling ChatGPT’s output for tailored results
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API Cost Management: Understand and optimize API usage to minimize costs and maximize efficiency.
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Project-Based Learning: Immerse yourself in hands-on projects, applying your knowledge to real-world scenarios, such as calorie counting, sentiment analysis, blog writing, phone wallpaper generation, and text summarization.
Ideal for:
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Developers seeking to harness ChatGPT and OpenAI API for language processing tasks.
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Beginners with no prior experience in ChatGPT or OpenAI API.
Prerequisites:
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Basic Python programming knowledge
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Computer with internet access
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Access to a Unix terminal
Enroll Now and Unleash the Power of Language Processing
Course Curriculum
Chapter 1: Introduction
Lecture 1: Syllabus
Lecture 2: Familiarize yourself with the Udemy User Interface
Lecture 3: Connect with Me
Lecture 4: AI Definitions and Acronyms
Chapter 2: A background on LLMs and Transformers
Lecture 1: What are Transformers and how do they power Generative AI
Lecture 2: Basic Prompt Engineering
Lecture 3: Zero shot and Few Shot Prompting
Lecture 4: Chain of Thought Prompting
Lecture 5: How to Evaluate Prompts and Models
Lecture 6: A Framework for writing Powerful Prompts
Lecture 7: Grounding LLMs for increased accuracy
Lecture 8: Controlling output formats with Exemplars
Lecture 9: Under the Hood: How Encoders allow LLMs to Process Prompts
Lecture 10: What is RAG (Retrieval Augmented Generation)
Lecture 11: What are AI Agents
Chapter 3: Setting up your Environment
Lecture 1: Creating an Account and getting a Secret Key
Lecture 2: Setting up your Environment
Lecture 3: Pricing and setting usage limits with OpenAI API
Lecture 4: OpenAI API Overview
Lecture 5: AI Application Architecture
Lecture 6: Building a RAG Pipeline from Scratch
Chapter 4: How to use the Completions API, and Chat API with Examples
Lecture 1: Update on the Completions API
Lecture 2: Translating an article with the OpenAI API
Lecture 3: Example: Translating an article with OpenAI API
Lecture 4: Summarizing with the OpenAI API
Lecture 5: Example: Summarizing with the OpenAI API
Lecture 6: Upgrading the OpenAI API
Lecture 7: Chat completion with the OpenAI API
Lecture 8: Example: Build your own Chatbot with the Chat completion API
Lecture 9: Sentiment Analysis and Classification with the OpenAI API
Lecture 10: Example: Sentiment Analysis and Classification with the OpenAI API
Lecture 11: Project: Building a chatbot for analyzing financial statements
Lecture 12: Understanding the script structure
Lecture 13: Understanding the LLM request
Lecture 14: Replacing the LLM request with another LLM like Gemini
Chapter 5: Using Multimodal functionality like Image Generation, and Speech API
Lecture 1: Overview of the Image Generation API
Lecture 2: Example: Use the Image Generation API to create Phone Wallpapers
Lecture 3: Overview of the Text to Speech API
Lecture 4: Example: Use the Text to Speech API to Transcribe Blog Posts
Lecture 5: How to use the Computer Vision API
Lecture 6: Example: Use the Computer Vision API to Count Calories
Chapter 6: Using Google Gemini API with large context windows
Lecture 1: Get Started with Gemini API in Google AI Studio
Lecture 2: Performing Chat Completion in Google Colab
Lecture 3: Use Cases of Large Context Windows
Lecture 4: Creating a Google Cloud Account and setting up Translate API
Lecture 5: Basic and Advance Translation with Cloud Translation API
Lecture 6: Code Walkthrough: Using Google Translate API to translate subtitles
Lecture 7: Example: Translate Subtitles to 3+ languages
Chapter 7: Fine Tuning, Deploying, and Ethics
Lecture 1: What is Fine Tuning and what is it used for
Lecture 2: Fine Tuning a Model with OpenAI API
Lecture 3: How to use GPT Builder to create custom GPTs
Lecture 4: Deploying an application with OpenAI API
Lecture 5: Dos and Don'ts with AI
Instructors
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Justin B
Software Engineer
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 2 votes
- 3 stars: 3 votes
- 4 stars: 19 votes
- 5 stars: 28 votes
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