Programming Fundamentals & Core Computer Science
In an era dominated by AI coding assistants, foundational computer science is more critical than ever. Master Big-O, data structures, concurrency, security, and clean architecture to audit and architect resilient production systems.
Programming Fundamentals — Timeline Gantt Chart
Click any stage row to jump straight into detailed topics, references, and notes.
Core Engineering Domains (6 Stages)
Core Computer Science & Data Structures
Big-O complexity, memory layouts, arrays, linked lists, hash tables, trees, graphs, and algorithmic problem-solving.
Writing Better Code & Software Design
Defensive error handling, schema validation, OOP, functional paradigms, clean code, DRY, and testing.
Tools & Development Environment
Terminal fluency, package managers, Git workflows, debugging techniques, and reading technical docs.
How Software Connects: Networks & Databases
HTTP/HTTPS, REST APIs, SQL databases, async event loops, caching, and authentication.
Professional Habits & Engineering Hygiene
Code reviews, telemetry & observability, security baselines, technical communication, and shipping projects.
AI-Era Engineering & Autonomous Workflows
Precision prompting, output auditing, ground-truth debugging, LLM API integration, and agentic workflows.
Review Pace
1 wksFast pass to fill syntax gaps and refresh basics. Optimize for speed here to build velocity for core modules.
Applied Pace
5 wksHands-on implementation and patterns. Expand what you know into practical production workflows and real-world architectures.
Core / Deep Pace
4 wksHighest cognitive load and time investment. Deep mathematical foundations, internals, kernel optimizations, and scale design.
How to get the most from this roadmap:
Tick topics as you review them, write quick notes in the built-in note pads for sticky recall, and test yourself out loud on the interview questions. Your progress is saved automatically to your browser.