Modern C++ from Scratch: The 2026 Beginner Path
by Ana Petrova
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Programming, AI and prompt-engineering courses written by working engineers. Filter by language, level, price or rating — buy once, get an instant email access link, keep it for life.
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Showing 1–24 of 36 courses
Learn C++20 the way it is actually written today, from first build to first real program.
Stop copying by accident and start writing C++ that owns its resources correctly.
The complete C++ career path: language, tooling, testing and three portfolio projects.
Write engine-grade C++ that respects cache lines, allocators and a 16-millisecond frame.
Go from zero to a hireable C# developer with .NET 9, real projects and modern tooling.
The three C# skills that separate a junior developer from a confident team member.
Build, secure, test and deploy a real HTTP API in C# without ceremony or boilerplate.
Translate everything you know from C# into idiomatic F#, one working example at a time.
Server-side JavaScript done properly, from the module system to a deployed HTTP service.
One continuous route from beginner JavaScript to a deployed full-stack application.
Design types that make invalid states unrepresentable and errors readable again.
Build React applications where props, state and data fetching are all fully typed.
Get past the borrow checker for good and ship a real command-line tool with Cargo.
Move from writing Rust that compiles to designing Rust APIs other people enjoy using.
Cross the safety boundary deliberately, bind to C, and prove your abstractions are free.
Complexity, structures and problem patterns taught for real code and real interviews.
Build, deploy and document six projects that prove you can do the job, not just the tutorial.
Ship model features that refuse the right things and never leak your system instructions.
Expose your own data and actions to assistants through MCP servers you write and control.
The full craft: prompt architecture, agent loops, evaluation harnesses and cost discipline.
Build a dataset, run a LoRA fine-tune, and prove it beats prompting for your narrow task.
The maths-light foundation that makes model behaviour, metrics and failures make sense.
Queues, caching, streaming, fallbacks and budgets: the architecture behind a reliable AI feature.
Design agents that plan, remember and stop, instead of looping until the budget is gone.