AI Creative Practice Course Overview

Use projects to connect AI models, agents, tools, and resources, then turn ideas into published work.

AI project delivery practice

Use a concrete project to define the problem, target users, and intended outcome first.
Select AI models, agents, development tools, and supporting resources around the project's needs.
Validate ideas and prototypes quickly while learning each tool's capabilities, limits, and best uses.
Locate the critical step when problems appear, choose a better technical path, and add source-code skills when needed.
Build, test, and deploy the project so the AI-assisted result becomes a real published product.
Iterate on features and experience through real feedback, creating a reusable delivery workflow.

AI creative practice course

Start with an idea you genuinely care about and use AI to make an interesting work of your own.
Find inspiration in existing open-source projects and create something new from a working foundation.
Begin with an open-source match-and-tower-defense game by migrating it unchanged and understanding its mechanics.
Keep the stable tower-defense and scoring systems while turning the matching mechanic into an English-learning experience.
Work with AI to reshape content, interactions, and features until the idea becomes a complete product.
Develop your own AI creation method through reusable prompts, tool combinations, and creative judgment.

Coming Soon

AI hardware course

Learn to build a personal AI compute environment: hardware selection, setup, and optimization.
Deploy and run open-source AI models locally to build your own AI assistant.
Learn model fine-tuning and customization for specific needs.
Explore multimodal models, AI agents, and other cutting-edge techniques.
Combine AI with hardware like smart home devices and robotics.
This track is in planning. We’ll curate the latest AI practices for deep learning.