Topics Worth
Revisiting

How distributed ledgers actually store and verify data — without the hype. Covers nodes, consensus, and why immutability matters in practice.

Specific tools like adaptive testing and automated feedback — what they actually do in a classroom versus what vendors claim.

Self-executing code on-chain — what triggers them, where they break, and three real-world use cases that don't involve speculation.

Training data, model types, and what "accuracy" actually measures — a grounded look at ML concepts for learners new to the field.

DIDs and verifiable credentials — how blockchain-based identity works and where it's being piloted in government and education systems.

Where bias enters a model and what auditing looks like in practice — not a philosophical debate but a technical walkthrough with examples.