# 學生對 圣彼得堡国立大学 提供的 Computational Geometry 的評價和反饋

3.8
22 個評分
8 條評論

## 課程概述

This course represents an introduction to computational geometry – a branch of algorithm theory that aims at solving problems about geometric objects. Its application areas include computer graphics, computer-aided design and geographic information systems, robotics, and many others. You will learn to apply to this end various algorithmic approaches, and asses their strong and weak points in a particular context, thus gaining an ability to choose the most appropriate method for a concrete problem. We will cover a number of core computational geometry tasks, such as testing point inclusion in a polygon, computing the convex hull of a point set, intersecting line segments, triangulating a polygon, and processing orthogonal range queries. Special attention will be paid to a proper representation of geometric primitives and evaluation of geometric predicates, which are crucial for an efficient implementation of an algorithm. Each module includes a selection of programming tasks that will help you both to strengthen the newly acquired knowledge and improve your competitive coding skills....

## 1 - Computational Geometry 的 8 個評論（共 8 個）

2020年3月24日

Extremely bad teaching style, Algorithms can not be taught like this through static Power points.

Its extremely important to do white boarding with thorough dry run of algorithms with examples..

Very disappointed with this course, I have completed almost 20 courses on coursera but unfortunately this is the first course where i have to give up.

2019年12月31日

Great opportunity to learn the algorithms. Challenging at times trying to figure out where your code went wrong, but you eventually get through it. Assignments can take a bit of time.

2020年5月18日

I was not very impressed. Another reviewer commented that this is a poor way to teach algorithms, and I agree: it is much too static, you have to see algorithms in action. Also, the video editing is frankly horrible. Every couple of seconds a transition between the lecturer and a whiteboard?!? How the hell can you look & listen & think? A more-static split screen would have been much better. Because I took this course during coronatime, I'll give it three stars... my inclination would otherwise be two stars.

2020年5月15日

Topics are interesting but the not all questions are answered in the discussion forums

2020年7月29日

Excellent course about a fascinating, sometimes difficult topic. The underlying ideas of the selected algorithms are well presented in the videos. The real challenge is to implement the details in the programming problems, required for the completion of the course.

There where some issues though: The video editing is really bad, making it sometimes very difficult to follow the lecturer. Deliberate use of the video player's pause and rewind functions helps a bit there.

The lecture slides were not available for download. Which was a problem when reviewing a certain topic before implementation.

In summary I still think that the combination of conceptional (theoretical) video lectures followed by the concrete implementation against an automated testing system is the best way to learn algorithms for any practitioner.

2020年6月24日

Some portions are taught in a great way,some in very average manner.If they can include the running animations for each algorithms,then i would have rated 5-star.Overall,a satisfactory experience.

2021年9月4日

This course was very frustrating and my only Coursera course I've dropped so far.

Negative points:

- as noted in several comments in the forums and in other reviews, the video editing is very frustrating. There's a looping effect every few seconds cycles through a full screen of the teacher, then a split-screen with the slide + teacher, with a very unhelpful and long effect. The timings of this effect are just automatic and not at all synchronized with the content, so in the middle of a formula in the slide, the effect comes up and it goes full screen to the teacher again, so you can't see the formula anymore. This happens tens of times per video, it is incredibly distracting and frustrating.

- the slides are not good, too static and without contextualization. For instance, there's a set of points in one slide. Then in the next slide one of the points changed, to show a different variation. Instead of showing clearly which point changed, you are left with the task of moving back and forth in the video to spot the difference. Then consider the effects mentioned in the previous item, and it just adds to the frustration.

- the teaching style is very formal and hard to understand, it sounds like reading a formal document and it is not at all engaging to listen to. Complex constructions that should only be used in written style are used in speech and it makes it so much harder to understand and plain boring. One small example (from the last video I saw before dropping): "Given a set S of n segments in the plane, find all the intersections of those. Why use this kind of construction? Why not just say "For a set S of n segments, find all the segment intersections". There are much worse examples in other videos.

- the teacher has a very strong accent, which made it very hard to understand, and the subtitles are auto-generated, and usually at the parts I didn't understand the subtitle was just wrong (because it made no sense)

2021年1月14日

Good but difficult course! The course is very algorithm-oriented course. Teaching method is a bit bland but the programming exercises are very good and difficult. It does not cover much of the theoretical aspects of computational geometry like Voronoi Diagrams etc.

The programming problem set is quite difficult and requires you to be very good at data structures and algorithms. Some of the exercises may also have many edge cases so you may need to look at the discussion forums frequently to try out certain test cases. Most of the exercises also require you to refer or search for external resources for figuring out how to implement them.

A better title for the course would be, 'Analysis of Computational Geometric Algorithms'.