Courses · published catalog
Every course lists its lessons, its content time, and whether a lab is provisioned for you when you launch it. The first lesson of each course is open to read before you sign in.
Courses are sold as part of a career path, which puts them in the order to take them. New to the subject? Start with a career path rather than a single course.
31 of 31 courses
Build a retrieval-based question-answering app in Python: model calls, tools, embeddings, RAG, evaluation and guardrails, all runnable offline.
Build the evaluation programme that decides whether a change to an AI application ships: golden sets, graders, metrics, regression gates, cost and safety.
Deploy a model-backed service the way it has to be run: threat-modelled, authenticated, rate-limited, logged, alerted, gated and rollable.
Analyse real, messy operational data with pandas and NumPy: load it, clean it, group and join it, work with dates, and turn it into saved charts and a written finding, hands-on in Python 3.12.
Learn SQL from your first SELECT to window functions, data cleaning and a quarterly business review, hands-on in PostgreSQL 16 on a realistic (synthetic) e-commerce database.
Design the tables a business reports from. Kimball-style dimensional modelling built end to end on PostgreSQL 16, from a real order system to a warehouse whose numbers reconcile.
Rebuild a pipeline's transformation layer with dbt-core on PostgreSQL 16 — sources, models, tests, snapshots, docs, environments and CI — against a result you already know is right.
Build trustworthy business reports end to end: write the SQL reporting layer in PostgreSQL 16, then model, measure and design a Power BI report on it and validate every number against the source.
Learn to run a Microsoft SQL Server 2022 instance the way a working DBA does: install and connect, secure logins, back up and restore, maintain, monitor, troubleshoot, automate, and plan for failure.
Build a real, re-runnable data pipeline in PostgreSQL 16 and Python 3.12: ingest messy files, validate and quarantine bad rows, model a star schema, and publish a checked data mart.
Own a database that has to survive a bad day. Recovery you have proved, access control the database enforces, plans you can read, and a standby — all on PostgreSQL 16.
Choose between the stores, the models and the movement patterns a data platform can be built from, and prove every choice on PostgreSQL 16 rather than asserting it.
Work IT support the way a good technician does: turn a request into a ticket and solve Windows problems with a method (define, reproduce, isolate, fix, verify, document) instead of guessing.
Administer an Ubuntu Server 24.04 machine from the console and over SSH: services, users, patching, storage, networking, nginx, automation and troubleshooting, on your own lab server.
Build switches, VLANs, routers, DHCP, DNS, NAT, a firewall and a VPN yourself on one Ubuntu lab machine, then troubleshoot seeded faults and hand over a small business network.
Run Windows Server the way an administrator does: install it, drive it with PowerShell, add roles and storage, build an isolated AD training domain, and manage users, Group Policy, DNS and DHCP.
Part 1 of the Azure Local program: reason about the platform, size it, secure it, prepare a deployment and deliver a defensible readiness package. Design-first; hosted labs in preparation.
Run a small internal platform with OpenTofu: declare infrastructure as code, gate every change through Git, keep secrets out of state, and operate what you built - without a public-cloud account.
Make two Ubuntu servers converge on a declared state with Ansible: inventories, idempotent playbooks, roles, Vault, linting, staged rollouts, rollback and drift detection.
Run a virtualization host yourself: build guests and OS containers, lay out storage and guest networks, snapshot, back up, restore, delegate access and plan maintenance on your own Ubuntu machine.
Learn how common web attacks work by finding them on a deliberately vulnerable app in an isolated lab, then fix and detect each one. Authorization and ethics come first, always.
Work a synthetic security incident end to end: triage the alert, read the logs, build a timeline, test a detection, preserve the evidence and write a report that does not overclaim.
Turn what an investigation learns into tested, version-controlled detections: write Sigma rules, test them positively and negatively, tune false positives, and run them on a lab-local Wazuh manager.
Work a synthetic host compromise through the NIST SP 800-61 Rev. 3 lifecycle: scoping, timeline, evidence, containment and eradication under change control, verified recovery and a blameless review.
Build the defences: a re-measurable hardening baseline, an nftables firewall, SSH and TLS from your own certificate authorities, abuse response, secret custody and tamper-evident logging.
Version a small Python service with Git, package it with Docker and Compose, and ship it through a fail-closed CI script, semantic-version releases and a practised rollback.
Learn Python the way operations people use it: scripts, files, APIs, tests and scheduled automation on Ubuntu Server 24.04.
Build a real HTTP API in Python with FastAPI: routing and validation, PostgreSQL with migrations, token authentication, tests against a test database, and a Docker Compose stack you can run.
Take a containerized service from Compose to a real Kubernetes cluster: Pods, Deployments, Services, Ingress, configuration, storage, resources, RBAC, network policy and a practised rollback.
Learn to test software the way professionals do — the test pyramid, pytest, fixtures, mocking, coverage, property-based testing, flaky-test hygiene, and gating a build on a fail-closed CI contract.
Design a service under load, growth and failure - and settle every argument with a running prototype you measured rather than a diagram you drew.
