Zurück zu Algorithmic Thinking (Part 1)

4.7

251 Bewertungen

•

48 Bewertungen

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"....

Sep 29, 2018

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.

Mar 08, 2018

This is where computer science truly starts, without the excessive preliminary math that usually scares most people away. Great course!

Filtern nach:

von Yair B

•Apr 30, 2016

The lectures will not get you near the understanding you'll need to complete the assignments. though the resources will.

The application is great, and hard so you'll actually have to understand the material.

You have been warned, this course is very different to the other courses in the specialization!

von Zoltán T

•Jul 18, 2019

There are some videos where the lecturer can't even use a computer. Then there are a homework which is completely unrelated to everything taught during the lectures. Regarding the practice examples, key information are missing from the descriptions. I ended up frozing my computer several times because the problem was very ill-written...

von Adam C

•Jul 09, 2019

Great course!

von Deepak V

•Jun 19, 2019

It was a good learning experience

von Max B

•Mar 21, 2019

Oh man, I hade so much fun in this course! The lectures and material is very good, and everything is wrapped up in much fun projects and applications where you will learn a lot. I especially enjoyed the more mathematical approach in AT compared to PoC and IIPP, and also the general class structure! Highly recommended!

von Gerardo G

•Mar 09, 2019

Great course, please offer an oline program to obtain an Rice university grade in science computer.

von Rudy H

•Mar 06, 2019

Prof. Luay is an excellent instructor, his approach is very well thought of and his explanation on the subject is very constructive and clear which is vital to the understanding of such subject. I am learning a ton and very thankful to all that involved.

von Rita I G

•Feb 07, 2019

Good course!!

von Olga T

•Sep 29, 2018

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.

von Artur P

•Sep 21, 2018

Some parts was hard and some not because of my own experience, in general very good course and only hard problems forces us to think.

von Jayadev H

•Aug 22, 2018

lectures are a bit on the slow side... not straight to the point and a bit repetative..

bfs we have already done in this spezialization.

but homework/project/applications are excellent!

makes up for the rest!

Thank you!

von 熊华东

•Aug 21, 2018

Very great course.At first i under estimate this course, but through this course i became stuggling in project and assignment. The depth and breadth of the course is wonderful.Maybe sometimes got stucked, but finally always found It's worthwhile spending hours on this course. This course drove me thinking and thinking. It should take some time to review. Sometimes i don't know how i finished

von Vern K

•Jul 26, 2018

Course and assignments were very well thought out and informative.

von Tairan Y

•May 13, 2018

very thoughtful course!

not easy by any means, but for sure learned a lot from the hard experience.

von Aaron M

•Mar 22, 2018

A step up in difficulty from the previous modules in this specialisation.

von Julian O

•Mar 21, 2018

Another excellent course in the specialization from Rice. Really interesting algorithms that were fun, and non-trivial, to implement. The plotting and comparison exercises are helpful for gaining insight.

von Márton A N

•Mar 08, 2018

This is where computer science truly starts, without the excessive preliminary math that usually scares most people away. Great course!

von Andrew F

•Mar 05, 2018

Another fantastic course from the team at Rice - thank you!

von Wynand

•Jan 11, 2018

Not quite the same level of energy presents in IIPP and Computing Principles. Also did not like the peer review projects, too messy.

von Siwei L

•Dec 23, 2017

Very helpful course!!

von Jaehwi C

•Dec 11, 2017

The best course to study computer science and algorithm for beginner!

von Michael B R

•Dec 08, 2017

Another great course in this specialization!

von Albert C G

•Dec 02, 2017

Great Class - Truly makes you think

von Alvin L

•Nov 22, 2017

What the professor explains he explains well, but there is a lot of stuff in the homework assignments that is not explained

von Edwin R

•Nov 12, 2017

The course content is well structured and the instructors' explanation is clear and concise!

Coursera arbeitet mit erstklassigen Universitäten und Organisationen zusammen, um Online-Kurse anzubieten und dadurch universellen Zugriff auf die weltweit beste Ausbildung zu ermöglichen.