Course catalog
Found: 2 courses · 15 in the catalog · all of them are recommended by moderation
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Version 1.0.0, 29 September 2026
level: advanced
A course for senior developers at Big 4 and other professional-services firms who already use GitHub Copilot — or are about to be told to — and want to use it as an engineer rather than as a faster autocomplete. Copilot in 2026 is an agent platform: agent mode and a Plan agent in Visual Studio 2026 and VS Code, specialised agents for debugging, profiling, testing and .NET modernisation, custom agents and skills your team keeps in the repository, MCP servers, cloud agents that return pull requests, and Copilot CLI in the terminal. The course teaches the skills that separate a senior from a passenger: engineering the context, splitting a task into a plan the agent can execute, reviewing an AI diff as critically as a colleague's, encoding team rules once so they work in every IDE, and knowing exactly what leaves the client's perimeter — and what it costs in AI Credits. Every capability is taught the same way: the pain that makes you reach for it, the capability itself, and its cost — including the uncomfortable ones, such as content exclusion not applying in agent mode, or a green test suite that an agent wrote to match its own bug. The mandatory track follows the official GH-300 (GitHub Copilot) exam outline, so the course doubles as certification preparation; optional units go deeper into Copilot CLI automation, hooks, model and cost engineering, and measuring real productivity. Labs use one sample repository — Aldervane Advisory LLP's ENGAGE platform — that opens in Visual Studio 2026, VS Code and the CLI alike; it is a public GitHub template (github.com/AndreyKuralekh/engage), so each learner starts from their own copy. Every lab also has a read-and-answer path for learners without a Copilot Business or Enterprise seat.
25 units · ~29.5 h without the optional units, ~34.5 h with them · material in English · author: Andrey Kuralekh
Version 1.1.0, 28 September 2026
level: intermediate
A hands-on course on using large language models across the test process: prompting for test analysis and design, evaluating what the model gives back, containing its risks, and rolling it out in an organisation that handles client data. Built around a professional-services engagement, where confidentiality and documented review are not optional. Assumes working knowledge of test design, test levels and defect management.
Testing and QA · 21 units · ~18.4 h · material in English · author: Andrey Kuralekh