Learn Algorithmic Thinking in Rice’s Online Course 5

Build simpler, more efficient computational solutions in this course on algorithms

Get trained on how experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language by using algorithmic thinking.

SEE THE COURSE

Algorithmic Thinking - Part 1 (Course 5)

In part 1 of this course, we will study the notion of algorithmic efficiency and consider its application to several problems from graph theory. As the central part of the course, students will implement several important graph algorithms in Python and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand the interaction between the algorithms and the structure of the data sets being analyzed by these algorithms.

Students should be comfortable writing intermediate-size (300+ line) programs in Python and have a basic understanding of searching, sorting, and recursion. Students should also have a solid math background that includes algebra, pre-calculus and a familiarity with the math concepts covered in "Principles of Computing".

Who should attend:

People interested in using algorithms to compare data and data structures
Intermediate programmers wishing to learn algorithms and algorithmic fundamentals
Students preparing for an advanced Computer Science course

You will be able to:

Break down problems into clear steps and formulate algorithmic strategies
Compare and select algorithms based on performance trade-offs
Articulate and analyze the principles behind algorithms and how they operate on graph data.

LECTURE SAMPLES

MEET YOUR RICE PROFESSORS

Luay Nakhleh

Luay Nakhleh is the William and Stephanie Sick Dean of the George R. Brown School of Engineering and Computing, as well as a Professor of Computer Science and of BioSciences at Rice University.

Scott Rixner

Scott Rixner is a Professor of Computer Science at Rice University. He is currently helping to lead the Master of Computer Science (100% Online) and Master of Data Science (100% Online) degree programs. Prior to joining Rice, he received his Ph.D. from MIT.

Joe D. Warren

Joe Warren is a Professor in the Department of Computer Science at Rice University.

Joe has led the development of several award-winning specializations on introductory programming on Coursera. Joe was an undergraduate at Rice from 1979-1983 and received his Ph.D. from Cornell in 1986. He has been a professor at Rice ever since and served as the Chair of the Department from 2008-2013.