Define the real problem, user, value and important boundaries.
Learn · Build · Evaluate · Present
Build 30 Ai projects from beginner to advanced
Follow complete projects you can build on your own computer. Begin with system thinking and progress through data, models, applications, deployment and a complete Ai product.
30 guided projects3 progressive levels1 expert capstone
The applied Ai learning spine
Every project adds a new layer
The sequence is designed to prevent random project hopping. Each stage introduces capabilities used by the projects that follow.
Problem Understanding→Data & Programming→Classical Ai→Machine Learning→Deep Learning→Generative Ai→Applications→Deployment & MLOps→Responsible Ai→Complete Ai Product
Thirty-project pathway
Choose your current level and continue in order
You may inspect every project, but the dependencies and “why this comes now” notes show the recommended route.
Local learning progress0 of 30 completed
Progress will stay in this browser. It is based on completed project milestones, not page visits.
No matching projects
Try another category, domain or coding level.
One repeatable build process
Every project runs from setup to portfolio evidence
The same end-to-end structure helps learners focus on new Ai ideas instead of relearning how to navigate each guide.
Prepare the local environment, starter files and validation test.
Inspect and prepare the data, documents, images or system inputs.
Create the simplest valid comparison before adding complexity.
Implement the main Ai method and complete workflow.
Measure quality, analyse errors and test practical usefulness.
Check privacy, fairness, security, misuse and human oversight.
Complete the README, report, demonstration and portfolio story.
Three routes inside every guide
Complete the core, then choose how far to extend it
Core Route
A CPU-friendly version with complete instructions, small data and expected outputs. Every learner should finish this route.
Extension Route
Add algorithms, features, evaluation or interface improvements after the core system works correctly.
Challenge Route
Solve a harder variation with fewer instructions and justify your own technical decisions.
Meaningful completion
Progress comes from evidence, not page scrolling
100%Complete project
10% Setup complete15% Data prepared15% Baseline complete25% Main system complete15% Evaluation complete10% Responsible Ai review10% Documentation and demo
Individual project standard
What every complete project guide will contain
Guides will only become available after their instructions, dependencies and expected outputs are tested from a clean local setup.
Project overview and final resultProject map and Dictionary linksRequirements and computer profileStarter files and folder structureArchitecture and data flowClean environment setupGuided milestones and codeExpected outputs and checkpointsEvaluation and error analysisResponsible Ai reviewTroubleshooting guidePortfolio deliverables and rubric
Project toolkit
Use the same practical resources throughout the pathway
The first guided project is available
Start Project 01Begin with Project 01: My First Ai Solution Canvas
This no-code project establishes the problem-framing and system-thinking foundation used throughout all 30 projects.