Full course description
Importance of Data Structures and Algorithms:
Algorithm is a step-by-step procedure, which defines a set of instructions to be executed in a certain order to get the desired output. Algorithms are generally created independent of underlying languages, i.e. an algorithm can be implemented in more than one programming language.
Data structure is a particular way of storing and organizing information in a computer so that it can be retrieved and used most productively. Different kinds of data structures are meant for different kinds of applications, and some are highly specialized to specific tasks.
Data structures and algorithms are patterns for solving problems. All computers rely on fundamental data structures and algorithms.
By the end of this short course, learners at a broad level will be able to:
- Objective 1: Define data structures such as heaps, balanced trees, and hash tables.
- Objective 2: Identify, construct, and clearly define a data structure that is useful for modeling a given problem.
- Objective 3: Combine fundamental data structures and algorithmic techniques in building a complete algorithmic solution to a given problem.
Who this course is designed for:
Students who are either admitted with prerequisites to graduate programs in Computer Science in the School of Computing, Informatics, and Decision Systems Engineering (CIDSE) at Arizona State University or students who are interested in becoming eligible to apply to one of those programs. Students may also complete this course if they have general interest in the topic area or are looking for a refresher on data structures and algorithms.
The course syllabus is available here.
What you'll receive:
You will receive a certificate of completion with your grade that you can attach in your graduate application for any graduate program within CIDSE. You must receive an 80% or higher in order to receive a certificate.
Meet the instructors
Ryan Meuth, Lecturer, CIDSE
In 2013, Ryan Meuth joined Arizona State University in the School of Computing, Informatics, and Decision System Engineering as a lecturer, focusing on Freshman engineering and the first year experience. Since then, he has additionally become the course coordinator for the CSE Capstone Program, ASU101-CSE, and FSE100-CSE. Meuth teaches FSE100-CSE, CSE Capstone, and a variety of CSE program courses focusing on embedded systems. Meuth was awarded the Top 5% Teaching Award in 2014, 2015 and 2016, as well as the Spirit of EPICS award in Spring 2015. Meuth's research interests are focused on the computer science classroom experience, and how that can be improved for all students.
Phillip Miller, Lecturer, CIDSE
Phill Miller joined the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University in 2014 after teaching computer science and software engineering courses for 14 years at the University of Advancing Technology in Tempe, AZ.