Java Object-Oriented Programming and Algorithms

This module covers the fundamentals of creating custom classes in Java, including class structure, defining attributes and methods, and understanding the role of classes as blueprints for objects in object-oriented programming.

This module explores the principle of encapsulation in object-oriented programming, teaching students how to hide internal implementation details and control access to class members using access modifiers and proper data encapsulation techniques.

This module introduces the concept of inheritance in Java, covering how classes can extend other classes to inherit properties and methods, and explores the use of abstract classes for creating template classes that cannot be instantiated directly.

This module covers two important concepts in Java: method overloading (creating multiple methods with the same name but different parameters) and method overriding (redefining inherited methods in subclasses to provide specific implementations).

This module introduces interfaces as contracts that define what methods a class must implement, and explores polymorphism - the ability of objects to take multiple forms and be treated as instances of their parent class or interface.

This module covers the fundamentals of Unified Modeling Language (UML) class diagrams, teaching students how to visually represent classes, their relationships, and system architecture using standardized notation for object-oriented design.

This module explores three fundamental sorting algorithms - selection sort, insertion sort, and merge sort - teaching students how each algorithm works, their implementation in Java, and their respective time and space complexities.

This module covers two essential search algorithms - linear search and binary search - explaining how to implement these algorithms in Java, when to use each approach, and analyzing their efficiency and performance characteristics.

This module introduces algorithm complexity analysis and Big O notation, teaching students how to evaluate and compare the efficiency of different algorithms by analyzing their time and space complexity in relation to input size.