Sabrina Goldfarb
GitHub
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Master the Future of Software Development
Learn AI-assisted engineering workflows and gain hands-on experience integrating generative content in your applications.
Total time: 23 hours, 47 minutes
Core Coursework
Take these in order
Prerequisite: The
Beginner Learning Path and
Node.js Learning Path
Up First
Start your journey into AI-assisted engineering with prompting techniques to help you generate high quality results from LLMs.
Up Next
Build a command-line agent from scratch. Learn key AI terminology, prompting strategies, how to manage the context window, and generating images with AI.
Up Next
Discover how AI-assisted tools like Cursor and Claude code can boost your productivity. Whether you’re doing quick component refactors, generating a project plan, or running end-to-end tests in the background, leveraging these tools can help you get your job done faster.
Up Next
The Model Context Protocol (MCP) standardizes how applications provide communicate with large language models (LLMs). Building an MCP server from scratch is a great way to understand the fundamentals, discover ways to integrate AI in common workflows, and future-proof your career.
Up Next
Machine Learning is foundational to AI, and hands-on experience training your own model strengthens your understanding. TensorFlow.js makes it easy to train custom models with JavaScript, right in your browser.
Up Next
Understanding the inner workings of prediction and neural networks builds a depth of knowledge that helps you adapt with the evolution of AI.
Elective Coursework
Optional, take in any order
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