Computer Science and information Technology Course

Lesson 1 • Networking and Internet Basics

Covers the layered network model, IP addressing, and core protocols. Prepares students to understand data communication used in every modern application.

Lesson 2 • Operating System Fundamentals

Introduces OS roles in resource management, process scheduling, and file systems. Provides context for how software interacts with hardware through system calls.

Lesson 3 • Introduction to Software and Abstraction

Explains how high-level code is translated to machine instructions via compilers and interpreters. Links abstraction layers to the hardware concepts covered earlier.

Lesson 4 • Binary and Data Representation

Covers number systems, encoding schemes, and how data is stored at the bit level. Establishes the numeric foundation required for all subsequent hardware and software topics.

Lesson 1 • Control Flow and Logic

Covers conditional statements, loops, and Boolean logic for directing program execution. Enables students to encode decision-making and repetition in code.

Lesson 2 • Debugging and Testing Practices

Covers systematic debugging strategies, unit testing, and error handling. Builds habits that reduce defects and improve code reliability throughout the course.

Lesson 3 • Variables, Types, and Expressions

Introduces primitive data types, variable declaration, and arithmetic expressions. Forms the syntactic and semantic base for all programming work in the course.

Lesson 4 • Arrays and Basic Data Structures

Introduces arrays, strings, and simple collections for storing multiple values. Connects data organization to algorithm efficiency introduced in the next chapter.

Lesson 1 • Polymorphism and Dynamic Dispatch

Covers compile-time and runtime polymorphism through overloading and overriding. Enables flexible, extensible designs that respond to varying object types uniformly.

Lesson 2 • Object-Oriented Design Principles

Introduces SOLID principles and common design heuristics for maintainable OOP code. Prepares students to evaluate and refactor class designs critically.

Lesson 3 • Introduction to Design Patterns

Presents creational, structural, and behavioral patterns as reusable OOP solutions. Connects abstract principles to concrete, industry-standard implementation templates.

Lesson 4 • Classes, Objects, and Encapsulation

Defines classes as blueprints and objects as instances, with fields and methods. Encapsulation protects internal state and is the entry point to OOP design.

Lesson 1 • Hash Tables and Hashing Techniques

Explains hash functions, collision resolution, and load factor management. Demonstrates O(1) average-case lookup that underpins databases and caching systems.

Lesson 2 • Graphs and Graph Algorithms

Represents graphs with adjacency lists and matrices, then applies BFS, DFS, and shortest-path algorithms. Connects to real-world network and dependency problems.

Lesson 3 • Sorting and Searching Algorithms

Analyzes and implements comparison-based and non-comparison sorting alongside binary search. Reinforces complexity analysis with concrete, measurable algorithm performance.

Lesson 4 • Complexity Analysis and Big-O Notation

Introduces time and space complexity using Big-O, Omega, and Theta notation. Provides the analytical framework used to evaluate every algorithm in this chapter.

Lesson 5 • Trees and Binary Search Trees

Covers tree terminology, traversal algorithms, and BST insertion and deletion. Establishes hierarchical data organization as a foundation for balanced trees and graphs.

Lesson 1 • Indexing, Transactions, and Concurrency

Covers B-tree indexes, ACID properties, and isolation levels for concurrent access. Prepares students to build reliable, high-performance database-backed applications.

Lesson 2 • Normalization and Schema Design

Applies first through third normal forms and BCNF to eliminate redundancy. Connects schema quality to query performance and data integrity outcomes.

Lesson 3 • Relational Data Modeling

Covers entity-relationship diagrams, relational schemas, and mapping rules. Establishes a rigorous data modeling vocabulary used throughout the database chapter.

Lesson 4 • SQL Querying and Manipulation

Teaches SELECT, JOIN, aggregation, and subqueries for data retrieval and modification. Builds practical query skills applied in every data-driven application.

Lesson 1 • API Design and Integration

Teaches RESTful and GraphQL API design principles, versioning, and documentation. Enables students to build interoperable services that integrate with external systems.

Lesson 2 • Requirements Engineering

Covers elicitation, specification, and validation of functional and non-functional requirements. Connects stakeholder needs to technical design decisions made later in the chapter.

Lesson 3 • Technical Debt and Code Quality

Defines technical debt, refactoring strategies, and code quality metrics. Equips students to maintain and improve existing codebases in professional environments.

Lesson 4 • System Architecture and Design Patterns

Introduces layered, microservices, event-driven, and serverless architectures with trade-offs. Builds on OOP design patterns to address system-level structural decisions.

Lesson 1 • Common Vulnerabilities and Exploits

Analyzes injection attacks, broken authentication, and insecure deserialization with examples. Connects vulnerability classes to the OWASP Top 10 framework for prioritization.

Lesson 2 • Cryptography Fundamentals

Covers symmetric and asymmetric encryption, hashing, and digital signatures. Builds the cryptographic vocabulary needed to evaluate and implement secure protocols.

Lesson 3 • Threat Modeling and Attack Surfaces

Introduces threat modeling frameworks, attacker profiles, and attack surface analysis. Provides a structured way to reason about security before writing a single line of code.

Lesson 4 • Authentication, Authorization, and Identity

Covers password hashing, multi-factor authentication, OAuth 2.0, and role-based access control. Enables students to implement identity systems that resist common credential attacks.

Lesson 1 • Cloud Service Models and Infrastructure

Distinguishes IaaS, PaaS, and SaaS models and maps them to deployment decisions. Establishes cloud vocabulary and cost-model thinking used throughout the chapter.

Lesson 2 • Monitoring, Logging, and Observability

Introduces metrics, distributed tracing, and structured logging for production visibility. Completes the deployment lifecycle by enabling rapid diagnosis of live system issues.

Lesson 3 • CI/CD Pipeline Design

Builds automated pipelines for building, testing, and deploying code on every commit. Connects software quality practices from earlier chapters to automated delivery workflows.

Lesson 4 • Containerization and Orchestration

Covers container images, Dockerfiles, and orchestration with container management platforms. Enables consistent, portable deployments across development and production environments.