Core Computer Science Fundamentals

Prepared for: Sasank

Great decision — if you want to be strong in AI, 3D, web dev, cybersecurity, and full-stack, then you must have a solid grip on Computer Science fundamentals. Below are the core topics with short notes so you know why each is important.

1. Mathematics for CS

  • Discrete Mathematics (logic, sets, relations, functions, combinatorics, graph theory)
  • Linear Algebra (vectors, matrices — super important for AI/ML, graphics)
  • Probability & Statistics (AI, ML, data science, cryptography)
  • Calculus (optimization in ML, algorithms, computer graphics)

2. Programming Fundamentals

  • Syntax, semantics, and control structures (loops, conditionals)
  • Functions & Recursion
  • Data types & Variables
  • Memory management (stack vs heap)
  • Error handling & Debugging
  • Object-Oriented Programming (classes, objects, inheritance, polymorphism, abstraction, encapsulation)
  • Functional Programming concepts (immutability, higher-order functions, pure functions)

3. Data Structures

  • Arrays, Strings, Linked Lists
  • Stacks, Queues, Deques
  • Trees (binary tree, BST, AVL, Heap, Trie)
  • Graphs (adjacency matrix/list, BFS, DFS, shortest path)
  • Hashing & Hash Tables
  • Priority Queues & Heaps
  • Advanced: Segment trees, Fenwick trees

4. Algorithms

  • Time & Space Complexity (Big O, Ω, Θ)
  • Sorting (bubble, insertion, merge, quick, heap)
  • Searching (binary search, linear search, hash-based)
  • Greedy algorithms
  • Divide & Conquer
  • Dynamic Programming (DP)
  • Graph Algorithms (Dijkstra, Bellman-Ford, Floyd-Warshall, A*, Kruskal, Prim)
  • Backtracking & Branch & Bound
  • String Algorithms (KMP, Rabin-Karp, suffix arrays)

5. Computer Architecture & Organization

  • Number Systems & Boolean Logic
  • Digital Circuits (logic gates, flip-flops)
  • CPU architecture (ALU, registers, cache, pipeline, instruction sets)
  • Memory hierarchy (cache, RAM, ROM, virtual memory)
  • Instruction cycles & machine language
  • Parallel processing basics (GPU, multicore)

6. Operating Systems

  • Processes & Threads
  • CPU Scheduling
  • Memory Management (paging, segmentation, virtual memory)
  • File Systems
  • Deadlocks & Concurrency
  • I/O systems
  • OS types (batch, real-time, distributed)

7. Computer Networks

  • OSI & TCP/IP Models
  • IP addressing, DNS, DHCP, NAT
  • Routing, Switching
  • Protocols (HTTP, HTTPS, FTP, SMTP, SSH, WebSockets)
  • Sockets & Ports
  • Wireless vs Wired Networks
  • Network Security Basics (encryption, firewalls, VPN, proxies)

8. Databases

  • Relational Databases (SQL) (tables, joins, normalization, ACID properties)
  • NoSQL Databases (MongoDB, Cassandra, Redis)
  • Transactions & Concurrency Control
  • Indexes & Query Optimization
  • Data Warehousing & Big Data basics

9. Software Engineering

  • SDLC models (Waterfall, Agile, DevOps)
  • Version Control Systems (Git, GitHub/GitLab)
  • Software Testing (unit, integration, system, acceptance)
  • Design Patterns (Singleton, Factory, Observer, MVC, etc.)
  • UML diagrams & Modeling
  • Requirement Analysis & Documentation

10. Theory of Computation

  • Finite Automata (DFA, NFA)
  • Regular Expressions & Grammars
  • Pushdown Automata & Context-Free Grammars
  • Turing Machines
  • Computability & Decidability (P vs NP problems)

11. Compiler Design

  • Lexical Analysis
  • Parsing (Top-down, Bottom-up)
  • Syntax Trees & Intermediate Code
  • Code Optimization
  • Code Generation
  • Assemblers, Interpreters, JIT

12. Cybersecurity Basics

  • Cryptography (symmetric, asymmetric, hashing)
  • Authentication & Authorization
  • Network Security (firewalls, IDS, IPS, VPNs)
  • Web Security (SQL injection, XSS, CSRF)
  • Ethical Hacking Basics

13. Artificial Intelligence & Machine Learning Fundamentals

  • Problem-solving (search algorithms: DFS, BFS, A*)
  • Knowledge Representation & Reasoning
  • Supervised vs Unsupervised Learning
  • Neural Networks & Deep Learning
  • Natural Language Processing
  • Computer Vision basics

14. Human-Computer Interaction (HCI)

  • UI/UX design principles
  • Accessibility & Usability
  • AR/VR basics for future projects

Why master these fundamentals?

If you master these fundamentals, you’ll have the strongest base for web development, AI/ML, cybersecurity, game & 3D engines, and systems programming.

Next step: I can create a step-by-step learning roadmap (topics ordered from basics → advanced) or turn this into a printable PDF / dark theme page. Which would you like?