Horizon University

Algebra 2 covers fundamental concepts in linear algebra, focusing on matrices and their applications.

• Chapter 1: Matrix Calculation and Linear Systems Introduces matrix operations and their role in solving linear systems.
• Chapter 2: Matrices and Linear Applications Explores the link between matrices and linear applications.
• Chapter 3: Endomorphism Reduction Examines endomorphisms diagonalization essential for simplifying linear operators.

This course is a Template, please add your description and change the course photo.

This course is a Template, please add your description and change the course photo.

This course provides a practical and conceptual introduction to the fundamental principles of Algorithms and Data Structures, essential for solving computational problems efficiently. Through a combination of theory and hands-on programming in C, students will learn how to design, implement, and analyze algorithms and data structures that form the backbone of computer science.
Key topics include iteration, recursion, divide-and-conquer techniques, pointers, arrays, linked lists, stacks, queues, trees, and algorithmic complexity analysis.

Learning Objectives

By the end of this course, students will be able to:

• Explain fundamental algorithmic concepts such as iteration, recursion, sorting, searching, and divide-and-conquer.

• Describe and apply principles of memory management (static and dynamic) in C.

• Analyze algorithm time complexity using Big O notation.

• Implement and manipulate fundamental data structures (arrays, linked lists, stacks, queues, trees).

• Apply iterative and recursive problem-solving techniques to design efficient solutions.

• Select appropriate data structures and algorithms for specific computational tasks.

• Demonstrate structured thinking, debugging, and code optimization skills.

• Evaluate trade-offs between time, space, and implementation paradigms when solving algorithmic problems.