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4.6

stars

125 Bewertungen

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14 Bewertungen

We’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day — the travelling salesman problem. The goal in this problem is to visit all the given places as quickly as possible. How to find an optimal solution to this problem quickly? We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science. Still, we’ll implement several solutions for real world instances of the travelling salesman problem. While designing these solutions, we will rely heavily on the material learned in the courses of the specialization: proof techniques, combinatorics, probability, graph theory. We’ll see several examples of using discrete mathematics ideas to get more and more efficient solutions.
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Jul 25, 2018

This final course in 5 course specialization is relatively easy one, although the last problem takes little bit time to solve. Provides good introduction to difficult to learn Delivery problem.

Nov 20, 2019

A fun conclusion to the specialization that brings all of the mathematics of combinatorics and graph theory together to show how it can be applied to some real world problems.

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von Aviral K

•Oct 27, 2018

Really liked the course; the python code in challenges is so well commented that it helped me learn a lot of math and code. Really appreciate the challenges and visual explanation he does by drawing graphs; specially in branch and bound. Could have made video instruction a little more friendly to people with low intuitive mathematical knowledge. Left a lot of gaps to be filled by self learning efforts through Google etc; as each video had a line or two that weren't explained up to the mark. I do take a lot of online courses on Udemy and I do love learning by myself and facing challenges; however I also really like when course instructors provide me clear and rock solid fundamental knowledge.

von Ishan B

•Jan 08, 2020

please make courses on how to code in different libraries, its highly necessary, because most of my friends wont even get the certificate even if they know how to solve problems just because they cant code

all in all 5 stars because im really exhausted

von David v R

•Feb 19, 2019

Interesting little course on a fascinating problem. The material doesn't start off too hard but gets more difficult in the dynamic programming and 2-approximation algorithm sections. This course is a good introduction to the TSP.

von Ashish D S

•Jul 25, 2018

This final course in 5 course specialization is relatively easy one, although the last problem takes little bit time to solve. Provides good introduction to difficult to learn Delivery problem.

von Aren T

•Nov 20, 2019

A fun conclusion to the specialization that brings all of the mathematics of combinatorics and graph theory together to show how it can be applied to some real world problems.

von Pedro M H V

•Jul 07, 2018

Great way to end a really detailed and engaging specialization that introduces anyone with a minimum background in Python to Algorithms.

von Ehsan S

•Jun 19, 2018

perfect course! very easy and interesting to follow. Pseudo-Algorithms were very useful and helped a lot to understand the concepts.

von satish k

•Dec 31, 2019

Very good course. If you are really good in python then go ahead with this course. Challenging questions to solve.

von Steven W

•Dec 22, 2017

This is a nice way to end the course and, seaways nicely into studying algorithms in general.

von Danielle G

•May 21, 2019

This course is to the point and challenges you with practical application.

von Michael L

•Dec 23, 2017

I really enjoyed this course.

von lcy9086

•Feb 03, 2019

Very Nice Course, Have fun!

von Miguel V

•Jan 14, 2020

This is a very nice course. I feel that a further explanation in the coding problems would be useful since sometimes you are not sure what one should return from the function.

von Konstantin K

•Dec 25, 2017

Good exercises!