# 学生对 俄罗斯国家研究型高等经济大学 提供的 Discrete Math and Analyzing Social Graphs 的评价和反馈

4.4
447 个评分
123 条评论

## 课程概述

The main goal of this online course is to introduce topics in Discrete Mathematics relevant to Data Analysis. We will start with a brief introduction to combinatorics, the branch of mathematics that studies how to count. Basics of this topic are critical for anyone working in Data Analysis or Computer Science. We will illustrate new knowledge, for example, by counting the number of features in data or by estimating the time required for a Python program to run. Next, we will apply our knowledge in combinatorics to study basic Probability Theory. Probability is everywhere in Data Analysis and we will study it in much more details later. Our goals for probability section in this course will be to give initial flavor of this field. Finally, we will study the combinatorial structure that is the most relevant for Data Analysis, namely graphs. Graphs can be found everywhere around us and we will provide you with numerous examples. We will mainly concentrate in this course on the graphs of social networks. We will provide you with relevant notions from the graph theory, illustrate them on the graphs of social networks and will study their basic properties. In the end of the course we will have a project related to social network graphs. As prerequisites we assume only basic math (e.g., we expect you to know what is a square or how to add fractions), basic programming in Python (functions, loops, recursion), common sense and curiosity. Our intended audience are all people that work or plan to work in Data Analysis, starting from motivated high school students. This Course is part of HSE University Master of Data Science degree program. Learn more about the admission into the program and how your Coursera work can be leveraged if accepted into the program here https://inlnk.ru/rj64e....

## 热门审阅

SS
Feb 27, 2020

this is a great course i love it and i learned many things like counting , basic of probability graphs\n\nthe first four weeks are amazing the last two weeks was hard to me but possible to solve

LR
Mar 30, 2020

The course is very understandable and assignments are very interesting and applicable. I love the way Russians teach mathematics, therefore I will continue watching courses from this University.

## 51 - Discrete Math and Analyzing Social Graphs 的 75 个评论（共 127 个）

Mar 14, 2020

Lessons are well-paced and instructors explain well

May 19, 2020

Very informative. Enjoyed doing assignments.

Mar 23, 2020

Very informative overview of Discrete Math.

Jan 9, 2021

Great course for data science learners!!!!

Oct 5, 2021

This Course is wonderfull.

Apr 30, 2020

I enjoyed the course.

Jul 14, 2020

Very good course!!

Jun 21, 2020

very good course!

Jun 21, 2020

Very good course

Feb 23, 2020

good session

Mar 6, 2021

Great Course

Jun 12, 2020

Great course

Oct 5, 2021

exceptional

Apr 2, 2021

ultra good

Aug 14, 2021

Excellent

Aug 2, 2021

very nice

Jul 5, 2020

Very good

May 23, 2020

Thank you

May 26, 2020

GOOD

Feb 24, 2020

good

Apr 26, 2020

I think the coverage of materials was very good. Sometimes there were holes in the presentation: a few grammar conventions (rather understandably) made for confusing moments. The quizzes sometimes presented things which were a bit less explained than they might have been... but then on the other hand they required a bit of independent looking-around, which was not bad. (One example was the 'number of isomorphisms' question, which was needlessly perplexing for someone just introduced to the formal definitions, and didn't know what sort of wrinkles might be added. Or maybe that was a good way of thinking downward from the presented idea, even if it was in itself very simple. I'm not sure.) Perhaps a few more visualizations would have been helpful, too... the ideas are abstract, but I (personally) find visualizations a good way in. Also, perhaps the python loops could have been more used. They are quite demonstrative -- the relation between tuples and permutations, in particular... but maybe there are some nice ways of doing that. Anyhow, I enjoyed the unsimple simplicity of it.

Aug 10, 2020

Mostly this was a very well explained course, especially where visuals are used (and just maths jargon). The teachers take the concepts and step you through them very clearly in most cases, though sometimes when the concepts get more complex, learners like myself would appreciate if it could not rushed through.

Mar 15, 2020

This course was challenging, but manageable. I like that 100% correct answers are required on the exams, which forces you to understand all the key points. The information in the course material relates enough to the exams, so if you understand the concepts, the assessment is quite doable.

Apr 4, 2020

Very good introduction for newbees. I like the style that it gives you a lot of quiz immediately after the teaching vedio. The only thing to improve is the introduction to the finnal assignment, which is some how misleading. But after consulting on the forum, I finally have it done.

Dec 1, 2020

This is an essential course for anyone looking to build up a strong foundation for mathematics for data science. The python codes are a joy to read and practice and the final assignment was a culmination of all things learned. Kudos to the instructor and mentors.