A little more confidence, every day
Find your next AI skill.
Explore the course, then put each idea into practice with short interactive lessons.
AI is already around you
Meet AI through small, familiar tasks.
8 activities →Your first safe conversation
Build a useful invitation, one choice at a time.
8 activities →Useful help, sensible limits
Choose useful assistance and check what matters.
8 activities →Learning from examples
Follow data to model to output, with no mathematics.
9 activities →How an answer is made
Why answers vary, and why plausible details can be invented.
7 activities →What the app can actually see
Inspect what a particular interaction really has available.
9 activities →Give a useful brief
Supply what a task needs, without relying on prompt tricks.
8 activities →Improve one thing at a time
Diagnose a disappointing result and revise it on purpose.
7 activities →Work from material you provide
Transform a source while preserving its meaning and limits.
9 activities →Check an answer
Use evidence to accept, correct or hold each claim.
8 activities →Protect people and information
Decide what to send, and what to do if too much went out.
8 activities →Images, voices and trust
Judge generated media, and refuse to be hurried.
9 activities →Learn with AI
Keep the thinking and the recall with the learner.
7 activities →Write and create with AI
Produce original work that still sounds like you.
7 activities →Plan and decide with AI
Treat a generated plan as a draft to be made workable.
8 activities →Tools and agents
Tell a suggestion from an action, and supervise the difference.
8 activities →AI, people and society
See the human choices behind a system's behaviour.
8 activities →Your everyday AI toolkit
Build a routine you will still follow when busy.
8 activities →Files and Markdown without mystery
Read and edit the small text files agents work from.
8 activities →Configuration is data with a format
Read small configuration files and keep credentials out of them.
9 activities →Different jobs for different models
Describe a model by the job it does, not by its design.
9 activities →Different ways to learn
Find where a training setup's signal comes from.
10 activities →The examples shape the model
Inspect a collection for the faults that matter.
10 activities →Use it: choose a model for the job
Turn three chapters of theory into one defensible decision.
7 activities →A neural network, one small part at a time
Trace a numerical model through connected layers.
9 activities →One training step at a time
Predict, measure, adjust — and which numbers are which.
10 activities →Learning that works on new examples
Judge generalisation with separate evidence.
9 activities →Use it: read a model card and find the gap
Find the absence that would change your decision.
7 activities →From text to small pieces
Tokens, identifiers, and what a budget is counted in.
7 activities →Representing relationships with numbers
Learned rows, similarity, shares and weighted mixing.
10 activities →The problem attention helps solve
Order, distance, and the fixed-summary bottleneck.
8 activities →Use it: budget a long document
Fit a long source into a small window, honestly.
7 activities →Attention: match, weight and mix
Query, key, value, scores, shares, and the weighted mixture.
10 activities →Attention across a sequence
Self and cross attention, order signals, masking, many heads.
9 activities →Build the Transformer picture
The block, the stack, and what 2017 actually contributed.
10 activities →Use it: diagnose a lost detail
Why a supplied fact went missing, and what to do about it.
7 activities →Language models have different designs
Encoder, decoder, encoder-decoder, embeddings, and the alternatives.
8 activities →Seeing, hearing and combining media
Pixels, patches, sound over time, and reading a capability card.
9 activities →Different ways to generate media
Denoising, latents, adversarial training and learned paths.
9 activities →Use it: choose a media capability
Direction, capability table, route, and a written disqualifier.
7 activities →From a base model to a useful assistant
Pretraining, fine-tuning, demonstrations, and where a change lives.
9 activities →Learning from feedback
Preferences, reward models, RLHF, DPO, and reward gaming.
9 activities →Why models become more capable
Data, capacity, compute, synthetic examples and answer-time work.
9 activities →Use it: judge a model release claim
The claim, the mechanism, the missing baseline, a fair line.
7 activities →Give a model useful outside information
Finding, chunking, ranking, grounding, freshness and permission.
9 activities →What happens while an answer is generated
Distributions, greedy, sampling, temperature, top-p, caching.
9 activities →Useful models can be smaller and simpler
Linear models, trees, ensembles, routing, distillation, precision.
9 activities →Use it: fix a wrong answer three ways
Classify the failure, repair in the right layer, attribute the fix.
8 activities →What does better actually mean?
Criteria, precision, recall, thresholds, subgroups and sample size.
9 activities →Test reliability beyond a headline score
Fair conditions, contamination, robustness, calibration, judges.
8 activities →Choose, monitor and keep learning
Model cards, licences, deployment routes, updates and monitoring.
8 activities →Use it: run a fair comparison
One task, one criterion, conditions held, and an honest limit.
7 activities →From hidden states to an answer
Vocabulary, scores, the output head, targets and stop reasons.
8 activities →What is actually in a conversation
Roles, precedence, templates, assembly, compaction and memory.
8 activities →Why responses take time and cost money
Prefill, decode, caches, memory limits and end-to-end budgets.
8 activities →Reasoning and adaptation after initial training
Few-shot, written steps, self-consistency, further training, unlearning.
7 activities →Use it: read your own request receipt
Split the time, attribute the cost, find the reuse, total the task.
7 activities →A workspace and its change history
Folders, repositories, diffs, commits, worktrees and publication.
8 activities →From a request to a tool result
APIs, tools, schemas, proposals, results and failure classes.
8 activities →The software around the model
The harness, workflows, plans, context selection, state and stops.
7 activities →Reliable actions over several steps
Retries, idempotency, permissions, sandboxes, handoffs, checkpoints.
9 activities →Which instruction file does what?
READMEs, agent guidance, scope, saved notes and what enforces nothing.
8 activities →A skill packages reusable know-how
Triggers, entrypoints, staged loading, resources and a small evaluation.
8 activities →Hooks, plugins and reusable systems
Events, scripts, packages, provenance, dependencies and versions.
8 activities →MCP connects an application to capabilities
Host, client, server, messages, versions and mutual support.
8 activities →Tools, resources and prompts
Operations, addresses, templates, prepared workflows and errors.
8 activities →Transport and authorized access
Local processes, endpoints, streaming, scopes, tokens and revocation.
9 activities →MCP and its neighboring ideas
APIs, tool calling, skills, retrieval, agent delegation and packages.
7 activities →Inspect, connect and troubleshoot
Narrow scope, provenance, manual inspection, selection and layers.
7 activities →Advanced MCP features and version changes
Progress, cancellation, input requests, interfaces, long tasks, eras.
9 activities →Brief a coding task
Observed problems, acceptance criteria, scope, exploration, reproducers and right-sized plans.
7 activities →Check the work an agent returns
Diffs, matching a check to the risk, regression tests, failure output and shared blind spots.
7 activities →Keep work recoverable and shareable
Checkpoints, worktrees, conflicts, handoff notes, pull requests and release verification.
8 activities →Meet Claude Code and start a session
Model against agent program, surfaces and execution location, setup stages, the right checkout and the first prompt.
7 activities →Guide Claude Code with context and extensions
Project guidance, diagnosing a rule that did not apply, skills, narrow connections, delegation and hooks.
7 activities →Claude Code use cases and recovery
Exploring a path, repairing a bug, narrow tests, refactors, documentation from real code, and stalled sessions.
8 activities →Meet Codex and choose a workspace
Product against model, surfaces, local and cloud state, access stages, the starting state and a first read.
7 activities →Guide Codex and inspect its reach
AGENTS.md discovery, overrides, skills, connected servers, the three permission dials and surviving compaction.
7 activities →Codex use cases and handoffs
Scoped changes, evidenced diagnosis, review against a contract, delegation, reports, and an honest close.
8 activities →Editor and cloud coding agents
Pending changes, assistance modes, briefs for detached runs, review surfaces and choosing by review fit.
7 activities →Other coding agents and interfaces
Terminal, editor and cloud examples, open clients with configured providers, explicit file context and frameworks.
7 activities →Start one small task in another tool
The same four checks in five unfamiliar products, and what makes a comparison between them fair.
7 activities →Useful agent work beyond a demo
Research briefs, data cleanup, rendered documents, live interfaces, automation limits and the simplest adequate system.
8 activities →