C# and .NET first, then Python, then AI systems.
A course that starts from zero and is built to end with a C#/.NET backend engineer who also writes Python and builds systems on AI models. Eight tiers and Job Preparation, practice beside every concept, and graded submissions that tell you what to fix. The AI tier is still being written — what is ready and what is not is listed below.
Each tier builds on the last, in one order, from your first program to the work of a senior engineer.
What a backend engineer does, setting up your machine, and how computers actually work: binary, text encoding, memory, the CPU, the operating system, the network.
Math literacy for engineers, then C# from your first line of code to C# 14 and .NET 10: types, methods, classes, collections, LINQ, generics, exceptions, async, testing, and concurrency. Then Git and the shell.
Discrete math, probability and statistics, and data structures and algorithms, built and measured in C#.
Networks and HTTP, SQL and schema design, ASP.NET Core, REST APIs, EF Core, caching with Redis, Docker, authentication, testing, CI/CD and deployment.
Python as a second language for a C# developer, its idioms and ecosystem, and a backend in FastAPI.
Building on AI models, classical machine learning, data engineering, deep learning, AI in production, and AI safety and evaluation. The outline is published; the lessons are not written yet.
Three applications built end to end: a dashboard app, a real-time chat app on SignalR, and a portfolio site with its own content API.
Architecture and scale, security, performance and observability, engineering practices, and owning problems end to end.
Timed challenges, an interview simulation, whiteboard problems, and a 72-hour take-home project.
Tiers 0–4, 6 and 7 and Job Preparation: 330 lessons, 1,191 exercises and 44 debugging challenges you can submit today.
Tier 5, AI Engineering: 81 lessons are outlined and not yet written.
300 more exercises in the ported units are on their pages but cannot be submitted yet, and grading is moving from AI review to automated tests.
The math unit's code examples are still in Java, and the projects' front-end sections still assume a front-end tier this course no longer teaches.
The why before the how, built on what earlier lessons taught.
Write your solution in your own editor and upload the files — real projects, not a browser sandbox.
A breakdown of correctness, quality, style and concepts, with what to fix.
Your dashboard tracks progress per part and points at what to revisit.
Upload your .cs files and get a review of correctness, code quality, idiomatic style, and whether you used what the lesson taught. Today Claude grades each one against the exercise's criteria; test-based grading is being built.
The mistakes you repeat are recorded across your submissions and quiz answers, with what to revisit.
Users, orders, invoices and accounts — examples from the services a backend engineer is hired to build.
Exercises sit right after the section that teaches them. You write code constantly.
No account is needed to read. Create a free account when you want to submit exercises for grading and track your progress.