Computer science foundations

A practical route through algorithms, data representation, operating systems, developer tools, and network protocols.

23 topics 4 checkpoints about 46 h beginner → intermediate

0 of 23 topics · milestone 1 of 4 Continue: Algorithmic complexity

The map

done you are here needs the checkpoint before it checkpoint

Milestone 1 · Algorithms and structures

0 of 6 topics · about 119 min

now Algorithmic complexity 21 min 2 Arrays and linked lists 20 min 3 Sorting and searching 20 min 4 Recursion 21 min 5 Hash maps 17 min 6 Trees and graphs 20 min

Checkpoint 1 unlocks M2

Milestone 2 · Data representation

0 of 5 topics · about 92 min

1 Unicode text 21 min 2 Regular expressions 18 min 3 Floating-point arithmetic 18 min 4 Dates and time 18 min 5 Internationalization 17 min

Checkpoint 2 unlocks M3

Milestone 3 · Systems and tools

0 of 6 topics · about 123 min

1 Linux 23 min 2 Processes and threads 17 min 3 Virtual memory 20 min 4 Shell basics 26 min 5 Pipes and redirection 17 min 6 Git's internal model 20 min

Checkpoint 3 unlocks M4

Milestone 4 · Network stack

0 of 6 topics · about 110 min

1 Network programming 18 min 2 DNS resolution 18 min 3 TLS connections 15 min 4 HTTP semantics 21 min 5 HTTP/2 20 min 6 WebSocket 18 min

Checkpoint 4 done

Why this order: Complexity and core data structures come first because they supply the cost models and invariants used throughout the path. Text, numbers, and time follow so programs can represent real inputs without silent corruption. Linux, processes, memory, shell pipelines, and Git then make execution and debugging concrete. Networking comes last because sockets, DNS, TLS, HTTP/2, and WebSocket all depend on those resource, boundary, and failure models.