AI for Beginners

Course overview

This 18-week introduction moves from symbolic reasoning, neural networks, vision, and language into machine learning, evaluation, clustering, production systems, edge deployment, and a bounded AI systems capstone. Weeks 1–12 preserve Microsoft source material and attribution; Weeks 13–18 are Robotnix-original applied chapters and labs.

Audience and pace

Grades 9–12. The scheduled course uses 18 five-lesson weeks at 210 instructional minutes per week.

What you will learn

• Explain how AI representations, models, data, evaluation, and systems interact.
• Inspect limits, uncertainty, bias, privacy, performance, and human authority rather than treating output as proof.
• Design and defend a bounded AI system with evidence, safeguards, and explicit limitations.

Course structure

The course covers symbolic AI; neural networks; computer vision; natural language processing; other AI techniques and ethics; learning from data; and AI systems/deployment. Interactive laboratories use bounded, local or supplied evidence rather than paid or remote services.

Learning evidence and assessment

Learners use diagrams, model and data reasoning, experiments, lab records, reviews, and reflections to show how a claim is supported. Assessment values the mechanism, evidence, limits, and next test—not only a correct-looking answer.

Expectations and boundaries

Do not upload personal or sensitive data, present generated material as verified fact, or use AI to replace ownership of course work. Review sources, test claims, disclose meaningful AI assistance, and respect course privacy and attribution rules.

Capstone

Build and Defend an AI System integrates a bounded model, data, architecture, tests, safeguards, and an evidence-based technical defense.

Access and support

The course reader and local browser labs support the core path. No paid AI service is required; alternatives and static/text fallbacks are supplied for instructional visuals.