Welcome to Collaborative Writing and Coding with OpenAI Canvas, built in partnership with OpenAI and taught by Karina Nguyen. This is a very short course, introduces a fun new tool that I think you'll enjoy trying. OpenAI Canvas is a new interface that provides a side by side workspace where you can collaboratively edit and refine text or code together with ChatGPT. This makes brainstorming and drafting and iterating on the text feel natural and more effective. In this course, you'll learn to use Canvas for writing and for coding. The instructor, Karina Nguyen, is one of the co-creators of Canvas. Welcome. Thanks, Andrew. Canvas makes both writing and coding with AI more fun and a lot easier. For writing, it allows you to highlight specific sections of your text for targeted edits. You can also adjust the length and complexity of your text. Additionally, Canvas provides tools to apply grammar checks and clarify enhancements. This iterative features make writing more flexible and efficient with Canvas. Lots of people are using AI to help with coding. Canvas has several tools that can help you create code better and faster. After creating the first version of your code, Canvas can review it and give suggestions for how to improve it. For example, if there's a syntax or logic error in your code, or if your code can be simplified or made faster, Canvas might be able to point this out. For myself, I'm sometimes a bit lazy of writing comments, and it think Canvas is great at that. It also helps with debugging by letting you add logs making it easier to find and fix problems. Another feature is the ability to translate code between different programing languages like Python, JavaScript and Java, with just a few clicks. You'll learn in-depth how all of these work by creating games like Space Battleship. You also see how you can use a picture, literally a picture of a database architecture, and input that and have Canvas write code for you to implement that architecture in code, and also write SQL queries against that. We'll also go behind the scenes and look at what it takes to train the model to create an interface like Canvas. I'll also touch on of the best practices with synthetic data to develop a model like this. Many people have worked to create this course. I'd like to thank Boris Power from OpenAI and from DeepLearning.AI Esmaeil Gragari and Geoff Ladwig also contributed to this course. This course is going to be a lot of fun. Let's go on to the next video to get started.