COURSE GOALS: This course will cover the theoretical aspects of algorithm design and analysis. Starting with a matching problem, we will first discuss the three central tasks of algorithm design: ...

Algorithm design strategies such as divide and conquer. Elementary techniques for analysis; asymptotic analysis, recursion equations, estimation methods, elementary combinatorial arguments.

Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis of ...

Quantum Algorithms Prerequisites Undergraduate algorithms (CSCI 3104), data structures (CSCI 2270), discrete mathematics (CSCI 2824) and two semesters of calculus, or equivalents. We will assume that ...

Getting Started Before you begin the course design process, you will need to determine what the gap or problem you are trying to address with your course is and how it fits into the bigger curriculum ...