
Explore how transformers power the GPT family by processing input in parallel with self-attention and positional encoding, offering advantages over rnn variants in handling long text.
Make sure you're using the right version of openai until the course is upgraded!
Move your OpenAI API key out of notebook or Python file, then load it with dot env values from a dot env file using python-dotenv.
Explore how model performance and pricing differ across OpenAI models, from simple tasks suitable for Ada or Babbage to high quality output with DaVinci 003, demonstrated in playground scenarios.
Learn to design prompts with precise output instructions and desired formats, such as JSON arrays or comma-separated lists, to produce code-ready data.
Explore common completion model use cases like sentiment analysis, summarization, and classification with practical prompts, including formatting and chunking large texts for cost-aware context management.
Develop a color palette generating website using the completion API with a Flask server and a frontend; craft prompts, render color swatches with hex codes, and copy colors to clipboard.
Implement a Flask post route /palette that reads form data, calls get colors with a completion API, and returns a JSON object containing the colors for the frontend.
Examine chat API pricing versus completion API, noting GPT-3.5 turbo is about ten times cheaper than text DaVinci 003 and uses the chat endpoint, while GPT-4 remains the most expensive.
Persist and manage a conversation history by accumulating user and assistant messages in a growing list and sending the full transcript with each OpenAI API call.
Translate javascript to python with GPT-4, test the results in the same notebook, and validate a min function, an email validation function, and word-capitalization.
Learn to use Tik Token to count tokens across encodings like KL100K base and P50K base for GPT-4 and GPT-3.5 Turbo, enabling pricing estimates and chunked book summarization.
Build a Python code reviewer tool that reads file content, wraps the review logic in a function, accepts a model via argparse, and outputs feedback at the command line.
Unleash the Power of AI: Master OpenAI's APIs, including GPT-4, DALL-E, and Whisper in this Comprehensive and Hands-On Course. This is a brand new course, recorded with GPT-4!
Step into the world of artificial intelligence and discover how to harness OpenAI's cutting-edge APIs, including GPT3, GPT-3.5, GPT4, DALL-E, and Whisper, to create groundbreaking applications and solutions. This immersive, project-driven course is designed for learners of all backgrounds and skill levels, providing a solid foundation in AI-driven development.
In this comprehensive course, you will:
Develop a deep understanding of OpenAI's generative models and their potential applications
Master GPT-4 for natural language processing, including text generation, summarization, translation, and more
Use GPT-4 to debug code, improve code, and even write code from scratch
Generate visually stunning images and artwork using DALL-E based on textual prompts
Convert spoken audio into accurate transcriptions and translations with the power of Whisper
Use AI Embeddings to distill, index, search, and compare text, unveiling the geometric power for comparing words, paragraphs, and documents
Real-World Projects for Practical Experience:
Create a dynamic Q&A Bot using GPT-4
Create a visual color palette search engine with GPT-4
Write an interactive code reviewing assistant with GPT-4
Create an AI-powered Spotify playlist generator
Analyze the sentiment of Reddit comments using GPT-4
Summarize books of any size into a couple of paragraphs
Create your own interactive, infinite Choose Your Own Adventure application with DALL-E and GPT-4
Generate an Emedding-Powered movie recommendation algorithm
Throughout the course, you will engage in hands-on projects and real-world examples, allowing you to immediately apply your newly-acquired knowledge and skills. We also delve into:
Best practices for prompt engineering, tokenization, and temperature settings
Strategies for optimizing API performance, error handling, and resource management
The ethical considerations and challenges associated with AI-driven development
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.
Embark on your AI journey and transform your skills with this comprehensive and engaging course. Enroll today and start unlocking the limitless potential of OpenAI's GPT-4, DALL-E, and Whisper APIs!