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 course builds on the principles that you learned in our Principles of Computing course and is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to real-world computational problems. 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 interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Recommended Background - 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".
This course is part of the Fundamentals of Computing Specialization
Algorithmic Thinking (Part 1)
Offered By
About this Course
Learner Career Outcomes
50%
67%
Skills you will gain
Learner Career Outcomes
50%
67%
100% online
Course 5 of 7 in the
Flexible deadlines
Intermediate Level
Approx. 20 hours to complete
English
Instructors
Luay Nakhleh
Associate Professor
52,633 Learners
5 Courses
Offered by
Rice University
Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy.
Syllabus - What you will learn from this course
Module 1 - Core Materials
What is Algorithmic Thinking?, class structure, graphs, brute-force algorithms
Modules 1 - Project and Application
Graph representations, plotting, analysis of citation graphs
Module 2 - Core Materials
Asymptotic analysis, "big O" notation, pseudocode, breadth-first search
Module 2 - Project and Application
Connected components, graph resilience, and analysis of computer networks
Top reviews from Algorithmic Thinking (Part 1)
very educational. I've learnt not only about graph theory but also how to use matplotlib and timeit libraries. The assignments were quite challengeable but rewarding.
The class is very useful, I already see the improvement in the codes that I write. And the assignments are very well-designed and truly helpful.
About the Fundamentals of Computing Specialization
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.