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Table of Contents

1.0 Introduction to Computer Science

1.1 What is Computer Science?

• 0.0.0 About this Wiki

• 1.1.1 Definition and Scope
• 1.1.2 Problem-Solving - Computational Thinking
• 1.1.3 Interdisciplinary Nature

1.2 History of Computing

• 1.2.1 Early Calculating Devices (Abacus, Pascaline, Leibniz Wheel)
• 1.2.2 Analytical Engine (Babbage & Lovelace)
• 1.2.3 Alan Turing: The Brilliant Mind Who Shaped Our Digital World
• 1.2.4 Early Electronic Computers (ENIAC, UNIVAC)
• 1.2.5 Transistors & Integrated Circuits
• 1.2.6 Personal Computers & the Internet

1.3 Key Figures in Computer Science

• 1.3.1 Ada Lovelace, Alan Turing, Grace Hopper, Dennis Ritchie, Linus Torvalds, etc.

1.4 Branches of Computer Science

• 1.4.1 Theoretical CS, Algorithms, Data Structures, AI, ML, Cybersecurity, Networking, etc.

2.0 Foundational Concepts

2.1 Data Representation

• 2.1.1 Binary Numbers (Bits, Bytes)
• 2.1.2 Number Systems (Decimal, Binary, Octal, Hexadecimal)
• 2.1.3 Character Encoding (ASCII, Unicode, UTF-8)
• 2.1.4 Image, Audio, and Video Representation (Basic)

2.2 Boolean Algebra & Logic Gates

• 2.2.1 AND, OR, NOT, XOR, NAND, NOR gates
• 2.2.2 Truth Tables
• 2.2.3 Boolean Expressions & Simplification

2.3 Algorithms & Pseudocode

• 2.3.1 Definition of an Algorithm
• 2.3.2 Characteristics of Good Algorithms
• 2.3.3 Representing Algorithms (Flowcharts, Pseudocode)

2.4 Computational Thinking

• 2.4.1 Decomposition
• 2.4.2 Pattern Recognition
• 2.4.3 Abstraction
• 2.4.4 Algorithms

3.0 Programming Fundamentals

3.1 Programming Paradigms

• 3.1.1 Procedural Programming
• 3.1.2 Object-Oriented Programming (OOP) - Basic Concepts
• 3.1.3 Functional Programming (Basic Concepts)

3.2 Data Types & Variables

• 3.2.1 Primitive Data Types (Integers, Floats, Booleans, Characters)
• 3.2.2 Reference Data Types (Strings, Objects)
• 3.2.3 Variable Declaration and Initialization

3.3 Control Structures

• 3.3.1 Conditional Statements (if, else if, else, switch)
• 3.3.2 Looping Constructs (for, while, do-while)

3.4 Functions/Methods

• 3.4.1 Definition and Purpose
• 3.4.2 Parameters and Return Values
• 3.4.3 Scope

3.5 Basic Data Structures

• 3.5.1 Arrays (One-dimensional, Multi-dimensional)
• 3.5.2 Strings (Manipulation, Common Operations)

3.6 Error Handling & Debugging

• 3.6.1 Types of Errors (Syntax, Runtime, Logic)
• 3.6.2 Exception Handling (try-catch)
• 3.6.3 Debugging Techniques and Tools

4.0 Data Structures Algorithms (DSA)

4.1 Data Structures

• 4.1.1 Linear Data Structures:
  • 4.1.1.1 Arrays (Fixed-size, Dynamic Arrays)
  • 4.1.1.2 Linked Lists (Singly, Doubly, Circular)
  • 4.1.1.3 Stacks (LIFO)
  • 4.1.1.4 Queues (FIFO, Priority Queues)

• 4.1.2 Non-Linear Data Structures:
  • 4.1.2.1 Trees (Binary Trees, Binary Search Trees, AVL Trees, Red-Black Trees)
  • 4.1.2.2 Graphs (Directed, Undirected, Weighted)
  • 4.1.2.3 Hash Tables (Hashing Functions, Collision Resolution)
  • 4.1.2.4 Heaps (Min-Heap, Max-Heap)
• 4.2 Algorithms
  • 4.2.1 Sorting Algorithms:
    • 4.2.1.1 Bubble Sort, Selection Sort, Insertion Sort
    • 4.2.1.2 Merge Sort, Quick Sort (Divide and Conquer)
    • 4.2.1.3 Heap Sort, Radix Sort
  • 4.2.2 Searching Algorithms:
    • 4.2.2.1 Linear Search
    • 4.2.2.2 Binary Search
  • 4.2.3 Graph Algorithms:
    • 4.2.3.1 Breadth-First Search (BFS)
    • 4.2.3.2 Depth-First Search (DFS)
    • 4.2.3.3 Dijkstra's Algorithm (Shortest Path)
    • 4.2.3.4 Minimum Spanning Trees (Prim's, Kruskal's)
  • 4.2.4 Dynamic Programming:
    • 4.2.4.1 Memoization, Tabulation
    • 4.2.4.2 Common DP Problems (Fibonacci, Knapsack)
  • 4.2.5 Recursion:
    • 4.2.5.1 Base Cases, Recursive Steps
    • 4.2.5.2. Tail Recursion
  • 4.2.6 Greedy Algorithms
• 5.0 Computer Architecture & Organization
  • 5.1 CPU Components
    • 5.1.1 Arithmetic Logic Unit (ALU)
    • 5.1.2 Control Unit (CU)
    • 5.1.3 Registers
    • 5.1.4 Instruction Cycle (Fetch, Decode, Execute, Store)
  • 5.2 Memory Hierarchy
    • 5.2.1 Cache Memory (L1, L2, L3)
    • 5.2.2 RAM (Random Access Memory)
    • 5.2.3 ROM (Read-Only Memory)
    • 5.2.4 Virtual Memory (Basic Concept)
  • 5.3 Input/Output Systems
    • 5.3.1 I/O Devices and Controllers
    • 5.3.2 Polling, Interrupts, DMA
  • 5.4 Instruction Sets
    • 5.4.1 RISC vs. CISC
  • 5.5 Assembly Language (Basic Concepts)
• 6.0 Operating Systems (OS)
  • 6.1 Role and Functions of an OS
    • 6.1.1 Resource Management, Process Management, Memory Management, File Management
  • 6.2 Process Management
    • 6.2.1 Processes vs. Threads
    • 6.2.2 Process States
    • 6.2.3 CPU Scheduling Algorithms (FCFS, SJF, Priority, Round Robin)
    • 6.2.4 Inter-Process Communication (IPC)
  • 6.2.5 Synchronization (Semaphores, Mutexes)
  • 6.3 Memory Management
    • 6.3.1 Paging, Segmentation
    • 6.3.2 Virtual Memory
    • 6.3.3 Page Replacement Algorithms
  • 6.4 File Systems
    • 6.4.1 File Organization, Directory Structures
    • 6.4.2 File Allocation Methods
  • 6.5 Concurrency & Deadlock
    • 6.5.1 Conditions for Deadlock
    • 6.5.2 Deadlock Prevention, Avoidance, Detection, Recovery
  • 7.0 Images & Graphics
    • 7.1 What is a Digital Image?
      • 7.1.1 Pixels and Resolution
      • 7.1.2 How Computers See Color (RGB, basic idea)
    • 7.2 Image File Formats
      • 7.2.1 JPG (for photos)
      • 7.2.2 PNG (for graphics, transparency)
      • 7.2.3 GIF (for simple animations, limited colors)
    • 7.3 Computer Graphics: Making Digital Art
      • 7.3.1 Creating Images (drawing, 3D models - simple concepts)
      • 7.3.2 Animation Basics (moving images)
    • 7.4 Image Processing: Changing Pictures
      • 7.4.1 Basic Edits (brightness, contrast, filters)
      • 7.4.2 Why We Process Images (fixing, enhancing, effects)
    • 7.5 Computer Vision: Teaching Computers to See (Brief, exciting examples)
      • 7.5.1 Facial Recognition
      • 7.5.2 Object Detection (self-driving cars, sorting)
  • 8.0 Networking & Internet
    • 8.1 Network Models
      • 8.1.1 OSI Model (7 Layers)
      • 8.1.2 TCP/IP Model (4/5 Layers)
  • 8.2 Protocols
    • 8.2.1 HTTP/HTTPS, FTP, SMTP, POP3, IMAP
    • 8.2.2 TCP (Reliable, Connection-Oriented)
    • 8.2.3 UDP (Unreliable, Connectionless)
    • 8.2.4 IP (Internet Protocol)
    • 8.2.5 DNS (Domain Name System)
  • 8.3 Network Topologies
    • 8.3.1 Bus, Star, Ring, Mesh
  • 8.4 Web Technologies (Basic Overview)
    • 8.4.1 HTML, CSS, JavaScript (Client-side)
    • 8.4.2 Web Servers, APIs
  • 9.0 Databases
    • 9.1 Database Types
      • 9.1.1 Relational Databases (SQL)
      • 9.1.2 NoSQL Databases (Key-Value, Document, Column-Family, Graph)
    • 9.2 Relational Database Concepts
      • 9.2.1 Tables, Rows, Columns
      • 9.2.2 Primary Keys, Foreign Keys
      • 9.2.3 Relationships (One-to-One, One-to-Many, Many-to-Many)
    • 9.3 SQL (Structured Query Language)
      • 9.3.1 CRUD Operations (SELECT, INSERT, UPDATE, DELETE)
      • 9.3.2 JOINs, Subqueries
      • 9.3.3 Data Definition Language (DDL)
      • 9.3.4 Data Manipulation Language (DML)
    • 9.4 Database Design
      • Normalization (1NF, 2NF, 3NF, BCNF)
      • Entity-Relationship (ER) Diagrams
    • 9.5 Database Management Systems (DBMS)
      • Examples (MySQL, PostgreSQL, Oracle, SQL Server) IX. Software Engineering
  • 10.0 Software Engineering
    • 9.1 Software Development Life Cycle (SDLC)
      • 9.1.1. Phases (Requirements, Design, Implementation, Testing, Deployment, Maintenance)
      • 10.1.2 Models (Waterfall, Iterative, Spiral)
    • 10.2 Agile Methodologies
      • 10.2.1 Scrum, Kanban
      • 10.2.2 User Stories, Sprints
    • 10.3 Version Control
      • 10.3.1 Git (Basic Commands: clone, add, commit, push, pull, branch, merge)
      • 10.3.2 GitHub/GitLab/Bitbucket (Remote Repositories)
    • 10.4 Software Testing
      • 10.4.1 Unit Testing, Integration Testing, System Testing, Acceptance Testing
      • 10.4.2 Test-Driven Development (TDD)
    • 10.5 Design Patterns
      • 10.5.1 Creational (Singleton, Factory)
      • 10.5.2 Structural (Adapter, Decorator)
      • 10.5.3 Behavioral (Observer, Strategy) X. Artificial Intelligence (AI) & Machine Learning (ML)
  • 11.0 Artificial Intelligence (AI) & Machine Learning
    • 11.1 Introduction to AI
      • 11.1.1 Strong AI vs. Weak AI
      • 11.1.2 Applications of AI
    • 11.2 Types of Machine Learning
      • 11.2.1 Supervised Learning (Regression, Classification)
      • 11.2.2 Unsupervised Learning (Clustering, Dimensionality Reduction)
        • 11.2.3 Reinforcement Learning
    • 11.3 Common ML Algorithms
      • 11.3.1 Linear Regression, Logistic Regression
      • 11.3.2 Decision Trees, Random Forests
      • 11.3.3 Support Vector Machines (SVM)
      • 11.3.4 K-Means Clustering
    • 10.4 Neural Networks & Deep Learning (Basic Concepts)
      • 11.4.1 Perceptrons, Layers
      • 11.4.2 Activation Functions
      • 11.4.3 Backpropagation (High-level)
      • 11.4.4 Convolutional Neural Networks (CNNs)
      • 11.4.5 Recurrent Neural Networks (RNNs)
    • 11.5 Natural Language Processing (NLP) / Computer Vision (CV)
      • 11.5.1 Basic tasks and applications
      • 11.5.2 Large Language Models (LLMs)
        • 11.5.2.1 Generative Pre-trained Transformers (GPT)
  • 12.0 Cybersecurity
    • 12.1 Fundamentals of Security
      • 12.1.1 Confidentiality, Integrity, Availability (CIA Triad)
      • 12.1.2 Authentication, Authorization, Accounting (AAA)
    • 12.2 Common Threats & Attacks
      • 12.2.1 Malware (Viruses, Worms, Ransomware)
      • 12.2.2 Phishing, Social Engineering
      • 12.2.3 Denial of Service (DoS) / Distributed Denial of Service (DDoS)
      • 12.2.4 Man-in-the-Middle Attacks
    • 12.3 Cryptography
      • 12.3.1 Symmetric vs. Asymmetric Encryption
      • 12.3.2 Hashing
      • 12.3.3 Digital Signatures
    • 12.4 Network Security
      • 12.4.1 Firewalls, Intrusion Detection/Prevention Systems (IDS/IPS)
      • 12.4.2 Virtual Private Networks (VPNs)
    • 12.5 Web Security
      • 12.5.1 Cross-Site Scripting (XSS)
      • 12.5.2 SQL Injection
      • 12.5.3 Cross-Site Request Forgery (CSRF) XII. Theoretical Computer Science
  • 13.0 Theoretical Computer Science
    • 13.1 Automata Theory
      • 13.1.1 Finite Automata (DFAs, NFAs)
      • 13.1.2 Regular Expressions
      • 13.1.3 Context-Free Grammars & Pushdown Automata
    • 13.2 Computability Theory
      • 13.2.1 Turing Machines
      • 13.2.2 Church-Turing Thesis
      • 13.2.3 Halting Problem (Undecidability)
    • 13.3 Complexity Theory
      • 13.3.1 Time and Space Complexity (Big O Notation revisited)
      • 13.3.2 P, NP, NP-Complete, NP-Hard XIII. Emerging Topics & Future Trends
  • 14.0 Emerging Topics and Future Trends
    • 14.1 Quantum Computing
      • 14.1.1 Basic Principles (Superposition, Entanglement)
      • 14.1.2 Qubits, Quantum Gates
    • 14.2 Blockchain & Distributed Ledger Technologies
      • 14.2.1 Decentralization, Cryptocurrencies
      • 14.2.2 Smart Contracts
    • 14.3 Cloud Computing
      • 14.3.1 IaaS, PaaS, SaaS
      • 14.3.2 Public, Private, Hybrid Clouds
    • 14.4 Big Data
      • 14.41 Volume, Velocity, Variety
      • 14.42 Hadoop, Spark (Basic Concepts)
    • 14.5 Ethical AI & Societal Impact
      • 14.51 Bias in AI, Privacy Concerns
      • 14.52 AI Safety and Governance

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