Algorithms II

Catalog description

This course provides an in-depth exploration of advanced algorithmic techniques essential for solving complex computational problems. Building on foundational knowledge of data structures and algorithms, students will study algorithm complexity analysis, including Big O, Big Theta, and Big Omega notations and complexity classes such as P, NP, and NP-complete. The course covers advanced sorting algorithms, divide-and-conquer strategies, dynamic programming, and greedy algorithms. Students will also examine fundamental graph algorithms, including shortest paths, spanning trees, and network flow solutions, with real-world optimization and data processing applications. Emphasis is placed on theoretical understanding and practical implementation, equipping students with the skills to design, implement, and evaluate efficient algorithmic solutions. Through hands-on coding and problem-solving, students will enhance their computational thinking and prepare for advanced coursework or careers in software development, data science, and related fields.