How to Learn Computer Science

A structured path through Computer Science — from first principles to confident mastery. Check off each milestone as you go.

Computer Science Learning Roadmap

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Estimated: 50 weeks

Programming Fundamentals

4-6 weeks

Learn a first programming language such as Python or JavaScript. Master variables, data types, control flow (if/else, loops), functions, and basic I/O. Practice writing small programs and solving beginner coding challenges.

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Data Structures

4-6 weeks

Study core data structures: arrays, linked lists, stacks, queues, hash tables, trees, and graphs. Understand their operations, time complexities, and when to use each one. Implement them from scratch to deepen understanding.

Algorithms and Complexity

5-7 weeks

Learn sorting algorithms (merge sort, quicksort), searching algorithms (binary search), graph algorithms (BFS, DFS, Dijkstra), and dynamic programming. Understand Big O notation and analyze algorithm efficiency.

Object-Oriented Programming and Design

3-4 weeks

Master OOP principles: encapsulation, abstraction, inheritance, and polymorphism. Study common design patterns (Singleton, Factory, Observer). Learn to write modular, maintainable, and testable code.

Databases and SQL

3-4 weeks

Learn relational database design, normalization, and SQL (SELECT, JOIN, GROUP BY, subqueries). Explore NoSQL databases like MongoDB. Understand indexing, transactions, and ACID properties.

Operating Systems and Networking

4-6 weeks

Study processes, threads, memory management, file systems, and scheduling. Learn networking fundamentals: TCP/IP, HTTP, DNS, sockets, and the OSI model. Understand how the internet works end to end.

Software Engineering Practices

3-5 weeks

Learn version control with Git, testing methodologies (unit, integration, end-to-end), CI/CD pipelines, Agile development, code review practices, and documentation. Build a collaborative project to apply these skills.

Specialization and Advanced Topics

8-12 weeks

Choose a specialization: web development, machine learning, cybersecurity, distributed systems, or mobile development. Study advanced topics like system design, cloud computing, and architecture patterns. Build portfolio projects.

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