Beginner
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Introduction to Computer

Computer Science Fundamentals

Eng-Abdiwahab Eng-Abdiwahab
Overview
Curriculum
  • 19 Sections
  • 166 Lessons
  • 1 Quiz
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Module 1: Orientation & tools
3 Lessons
  1. Module 1: Orientation & tools
  2. Orientation
  3. Tools
Module 2: Number systems & data representation
6 Lessons
  1. What are Number Systems & Data Representation?
  2. 1. Number Systems
  3. Decimal Number System (Base 10)
  4. Octal Number System (Base 8)
  5. 2. Data Representation
  6. 3. Why Number Systems & Data Representation Are Important
Module 3: Logic, proofs & discrete fundamentals
4 Lessons
  1. What is Logic, Proofs & Discrete Fundamentals?
  2. 1. Logic
  3. 2. Proofs
  4. 3. Discrete Fundamentals
Module 4: Sets, functions, relations & counting
6 Lessons
  1. What are Sets, Functions, Relations & Counting?
  2. 1. Sets
  3. 2. Functions
  4. 3. Relations
  5. 4. Counting (Combinatorics)
  6. Simple definition
Module 5: Introduction to algorithms & complexity
6 Lessons
  1. 1. What is an Algorithm?
  2. 2. Characteristics of a Good Algorithm
  3. 3. Algorithm Complexity
  4. 4. Big-O Notation
  5. 5. Why Algorithms & Complexity Are Important
  6. Simple definition
Module 6: Data structures I: arrays, lists, stacks, queues
10 Lessons
  1. Data Structures I: Arrays, Lists, Stacks, Queues
  2. 1. Arrays
  3. Time Complexity
  4. 2. Lists (Linked Lists)
  5. Time Complexity
  6. 3. Stacks
  7. Time Complexity
  8. 4. Queues
  9. Comparison of Data Structures
  10. Summary
Module 7: Data structures II: trees & heaps
12 Lessons
  1. Data Structures II: Trees & Heaps
  2. 1. Trees
  3. 2. Types of Trees
  4. 2.2 Binary Search Tree (BST)
  5. 3. Tree Traversal
  6. 4. Heap Data Structure
  7. 5. Heap Operations
  8. 6. Heap Implementation
  9. 7. Heap Time Complexity
  10. 8. Applications of Trees & Heaps
  11. 9. Comparison
  12. Summary
Module 8: Graphs & basic graph algorithms
14 Lessons
  1. Graphs & Basic Graph Algorithms
  2. 1. What is a Graph?
  3. 2. Graph Terminology
  4. 3. Types of Graphs
  5. 3.2 Directed Graph (Digraph)
  6. 3.3 Weighted Graph
  7. 4. Graph Representation
  8. 4.2 Adjacency List
  9. 5. Graph Traversal Algorithms
  10. 5.2 Depth-First Search (DFS)
  11. 6. Shortest Path Algorithm (Intro)
  12. 7. Minimum Spanning Tree (Intro)
  13. 8. Real-World Applications of Graphs
  14. Summary
Module 9: Sorting & advanced algorithmic techniques
17 Lessons
  1. Sorting & Advanced Algorithmic Techniques
  2. 1. What is Sorting?
  3. 2. Types of Sorting Algorithms
  4. 3. Bubble Sort
  5. 4. Selection Sort
  6. 5. Insertion Sort
  7. 6. Merge Sort
  8. 7. Quick Sort
  9. 8. Heap Sort
  10. 9. Comparison of Sorting Algorithms
  11. 10. Advanced Algorithmic Techniques
  12. 10.2 Dynamic Programming (DP)
  13. 10.3 Greedy Algorithms
  14. 10.4 Backtracking
  15. 10.5 Branch and Bound
  16. 11. Real-World Applications
  17. Summary
Module 10: Theory of computation (intro)
9 Lessons
  1. Theory of Computation (Introduction)
  2. 📘 Visual idea of computation models
  3. 📘 Visual idea of computation models
  4. 1. Why Study Theory of Computation?
  5. 2. Main Areas of Theory of Computation
  6. 3. Turing Machines
  7. 3. Important Concepts
  8. 4. Real-World Importance
  9. 5. Simple Definition
Module 11: Programming languages foundations
10 Lessons
  1. Programming Languages Foundations
  2. 📘 Programming Language Concepts
  3. 📘 Programming Language Concepts
  4. 1. What is a Programming Language?
  5. 2. Main Areas of Programming Language Foundations
  6. 3. Type Systems
  7. 4. Memory Model
  8. 5. Programming Paradigms
  9. 6. Why Programming Language Foundations Matter
  10. Simple Definition
Module 12: Computer architecture & systems basics
12 Lessons
  1. Computer Architecture & Systems Basics
  2. 🖥️ Computer Architecture Overview
  3. 🖥️ Computer Architecture Overview
  4. 1. What is Computer Architecture?
  5. 2. Von Neumann Architecture
  6. 3. Instruction Execution Cycle
  7. 4. Memory Hierarchy
  8. 5. Performance Metrics
  9. 6. Parallel Processing Basics
  10. 7. Hardware–Software Interaction
  11. 8. Why Computer Architecture is Important
  12. Simple Definition
Module 13: Operating systems fundamentals
12 Lessons
  1. Operating Systems Fundamentals
  2. 💻 Operating System Structure
  3. 💻 Operating System Structure
  4. 1. What is an Operating System?
  5. 2. Main Functions of Operating Systems
  6. 3. Process & Thread Basics
  7. 4. CPU Scheduling
  8. 5. Virtual Memory
  9. 6. Synchronization & Deadlock
  10. 7. File Systems
  11. 8. Why Operating Systems Are Important
  12. Simple Definition
Module 14: Computer networks essentials
12 Lessons
  1. Computer Networks Essentials
  2. 🌐 Network Structure Overview
  3. 1. What is a Computer Network?
  4. 2. Network Models
  5. 3. Types of Networks
  6. 4. Network Devices
  7. 5. IP Addressing
  8. 6. Network Protocols
  9. 7. Basic Networking Concepts
  10. 8. Network Security Basics
  11. 9. Why Computer Networks Are Important
  12. Simple Definition
Module 15: Databases & data modelling
11 Lessons
  1. Databases & Data Modelling
  2. 🗄️ Database System Overview
  3. 1. What is a Database?
  4. 2. Data Modelling
  5. 3. Relational Database Model
  6. 4. SQL (Structured Query Language)
  7. 5. Database Normalization
  8. 6. Transactions & ACID Properties
  9. 7. Indexing
  10. 8. Database Applications
  11. Simple Definition
Module 16: Security fundamentals & best practices
12 Lessons
  1. Security Fundamentals & Best Practices
  2. 🔐 Security Concept Overview
  3. 1. Information Security Goals (CIA Model)
  4. 2. Authentication and Authorization
  5. 3. Cryptography Basics
  6. 4. Common Security Threats
  7. 5. Network Security
  8. 6. Secure Coding Practices
  9. 7. Backup and Recovery
  10. 8. Best Security Practices
  11. 9. Importance of Security Fundamentals
  12. Simple Definition
Module 17: Capstone project week & review
9 Lessons
  1. Capstone Project Week & Review
  2. Capstone Project Overview
  3. 1. Purpose of Capstone Project
  4. 2. What Students Do in Capstone Week
  5. 3. Project Presentation
  6. 4. Review Process
  7. 5. Skills Developed
  8. 6. Importance of Capstone Project
  9. Simple Definition
Suggested reading & resources
1 Lesson
  1. Suggested reading & resources
Exam
1 Quiz
  1. Final

Course Description Computer Science Fundamentals

Computer Science Fundamentals is an introductory course designed to provide students with a strong theoretical and practical foundation in computing. The course covers essential concepts of computer science, including data representation, algorithms, programming principles, computer systems, networking basics, databases, and cybersecurity fundamentals.

The course introduces how computers process information, how software is designed, and how digital systems communicate. Students will learn core mathematical and logical foundations used in computing, including logic, proofs, discrete mathematics, and algorithmic thinking.

Programming language theory and basic software development concepts are also explored. Students gain understanding of syntax, semantics, compilation, memory models, and programming paradigms that form the basis of modern software engineering.

The course also provides knowledge about computer architecture, operating system principles, and hardware software interaction. Topics such as CPU operation, process management, memory hierarchy, and file systems help students understand how computing systems function internally.

Networking fundamentals are introduced to explain how computers communicate through protocols, IP addressing, and network structures. Security fundamentals are included to help students understand data protection, authentication, encryption, and safe computing practices. Guidelines from organizations such as Open Web Application Security Project (OWASP) are often referenced for modern security awareness.

Database theory and data modelling concepts teach students how information is structured, stored, and managed in database systems. Students also study basic artificial intelligence ideas and advanced algorithmic thinking.

A major component of the course is the capstone project, where students apply their knowledge to build a practical computing solution.

Upon completion, students will have a solid understanding of computer science principles and will be prepared for further studies in software engineering, cybersecurity, data science, or advanced computing fields.

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