Algorithmic Thinking (Part 2)

This Specialization covers much of the material that first-year Computer Science students take at Rice University. Students learn sophisticated programming skills in Python from the ground up and apply these skills in building more than 20 fun projects. The Specialization concludes with a Capstone exam that allows the students to demonstrate the range of knowledge that they have acquired in the Specialization.

Created by: Luay Nakhleh

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Overall Score : 92 / 100

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Course Description

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms.Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.

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Instructor Details

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Luay Nakhleh received a BSc degree in Computer Science from the Technion (Israel) in 1996, a Master's degree in Computer Science from Texas A&M University in 1998, and a PhD degree in Computer Science from UT Austin in May 2004 (Advisor: Prof. Tandy Warnow). While at UT Austin, he received the Outstanding Doctoral Dissertation Award, the Bert Kay Dissertation Award, the Texas Excellence Teaching Award, and the Outstanding Teaching Assistant Award. Luay joined the Computer Science department at Rice University as an Assistant Professor in July 2004, and was promoted to Associate Professor, with tenure, effective July 2010. While at Rice, he received the DOE CAREER award in 2006, the NSF CAREER award in 2009, the Phi Beta Kappa Teaching award in 2009, an Alfred P. Sloan Research Fellowship in 2010 (in the Molecular logy category), and a John P. Simon Guggenheim Foundation Fellowship in 2012 (in the Organismic logy and Ecology category).

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Reviews

4.6

28 total reviews

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By Rishab R on 26-Jul-18

Course and assignments were very well thought out and informative.

By Roberto M P F M on 10-Jun-19

The content is great, but it is taking ages for me to have my last assignment reviewed

By Martin W on 3-Feb-17

Really like the mix of theory and practical application

By Jaehwi C on 11-Jan-18

Great course to learning computer science!

By Ganapathi N K on 11-Nov-17

Fantastic course

By Rohan G L on 25-Mar-18

Great class...Luay's lectures and problem sets were a great continuation to what Joe and Scott started. I suppose I will get started on Course 7 shortly.

By Rachel K on 19-Aug-17

Challenging and enjoyable!

By Siwei L on 25-Dec-17

Great course!!!

By Tianyi Z on 27-Oct-16

Great course, problem solving oriented

By Jin X on 2-May-16

Love it.

By Michael B R on 16-Dec-17

Yet another great course in this specialization

By Yvan S on 19-Oct-16

The last awesome course on computing science.