Вернуться к Discrete Math and Analyzing Social Graphs

# Отзывы учащихся о курсе Discrete Math and Analyzing Social Graphs от партнера НИУ ВШЭ

4.4
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Оценки: 449
Рецензии: 123

## О курсе

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....

## Лучшие рецензии

LR
30 мар. 2020 г.

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.

SS
27 февр. 2020 г.

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

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## 1–25 из 127 отзывов о курсе Discrete Math and Analyzing Social Graphs

14 февр. 2020 г.

Overall course is OK, but it has few problems:

1) The way of presenting of the material. It is clear that target to cover 2-3 area of discrete mathematics under 5 weeks (not counting latest week for Python assignment) is very optimistic, but better to make more weeks or increase amount of video rather than it is in the course. All materials are extremely short, just giving you few formulas and then in very-very easy graded task you apply this formula.

In fact, instead of teaching math, this course is teaching you to apply few formulas to very standard problems to get the result.

I would prefer having let's say 10 weeks each with double amount of video, but with a proper mathematical introduction.

2) Final week and Python assignment has absolutely nothing to do with the previous 5 weeks, looks really weird and not prepared

автор: Ha T T

7 февр. 2020 г.

автор: MD. A I S

28 июля 2020 г.

Not a good course. I don't recommend it to anyone. The reasons are below :1 ) Don't fully cover topics 2) make topics complex unnecessary 3) course final programming assignment are so poor designed because of submission process. 4) i don't know how some people come with idea that combinatorics and graph theory are taught by some slides. very ridiculous decision because you can't teach mathematics without interactive writing. P.S : lightboard representation was great in probability week, they should try it in near future. I just wondering about those who are assigned in this master's course. a huge regret will come down to them. I planned to finish the whole specialization but after such horrendous experience, i quit this plan after finishing this course only.

автор: Priyank S

12 авг. 2020 г.

Pathethic course. Just hated the course, nothing to do with my expertise or what i plan to do by learning data science.

автор: Muddasser N

23 февр. 2020 г.

Very good course and must be taken for good understanding of the underlying concepts. Instructors are really good and knowledgeable. However, more material to read and study could be provided for those who like to get more in-depth understanding of the subject matter at hand.

автор: AHMED S

28 февр. 2020 г.

this is a great course i love it and i learned many things like counting , basic of probability graphs

the first four weeks are amazing the last two weeks was hard to me but possible to solve

автор: Stud 2

5 нояб. 2020 г.

Stop reading from slides please explain on a whiteboard and provide the slides as supplementary materials

автор: Deleted A

14 янв. 2020 г.

Great Course. Concise and Easy to Follow. Final Assignment should have been more comprehensive.

автор: UC O

15 дек. 2020 г.

I struggled to understand his english. I think it's best he writes what needs to be said and let and english speaker for him.

автор: Lala R

31 мар. 2020 г.

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.

автор: Bharani J

26 янв. 2021 г.

Concisely made course. The questions in the quiz tested the understanding of notions introduced in the Lectures. Amazing work by the Teaching staff too who replies promptly. Thanks overall

автор: Xingxing T

3 апр. 2020 г.

This course is very helpful to gain analyzing skills and mindset with discrete math. Some math concepts I struggled was easy to absorb during the course.

автор: Matthew S

8 окт. 2020 г.

This course was extremely helpful in regards to understanding and applying the basic math used in data science. The professors walk you through set notation, combinatorics (counting methods and binomial theorem), discrete probability, and graph theory step-by-step from basic observations to more complex applications, ending in a final project that wraps up the course quite well. I thoroughly enjoyed this course and the added mini-guide at the end that help considerably with completing the final project.

автор: Caio C

29 мая 2021 г.

O curso oferece exatamente o prometido em sua descrição, de forma didática e fornecendo o feedback e material necessários para o estudo e realização das tarefas. A única sugestão que posso oferecer é: um vídeo básico de como baixar o python e os módulos utilizados na última tarefa. Isso não me atrapalhou em momento algum, mas acho que facilitaria para pessoas com menos contato com este tipo de processo. Obrigado pelo curso!

автор: Svetlana B

27 мая 2021 г.

I really enjoyed the course. I took this course to fill in the blanks as I already have a certificate in Data Analytics from UT Austin. I think this course will work for most learners. As with every course, if you do not understand something, there is a ton of Utube videos for every level. If someone feels not challenged enough, the sky is your limit, and nothing should stop you to climb higher.

автор: David E

20 июня 2021 г.

T​his is a great course for an introduction to combinations, permutations, graphs and social graphs. If it's been a while since you've done some maths, it may take you a little longer than the suggested time to get up to speed. An ability to write software code is required - do not ignore the Python is a prerequesite. I enjoyed all the lecturers and the content.

автор: Ana M

18 мая 2020 г.

This was an amazing review of all the topics necessary to understand probability theory and social graphs. Wish I had seen this before I started my thesis on Social Network Analysis. It's a really good introduction to SNA. I also loved the summary of lectures provided by the instructors. Thank you so much!

автор: Владимир Р

25 мая 2021 г.

Спасибо. Очень интересный курс. Много полезной информации, реально даже не думал, что настолько затягивает... Спасибо огромное! И дальше буду получать у вас знания. Надеюсь, что они принесут значимый результат для моего профессионального роста по специальности Data Science

автор: rajasekaran

21 мая 2020 г.

This is a very useful course for anyone beginning to learn or trying to refresh basics in combinatorics, probability and graph theory. The content is very simple esp. combinatorics and probability. i was able to apply the learning quickly in programming situations.

автор: Jeff D

30 сент. 2020 г.

I love this course, for me, the course is very hard especially I'm a health professional and in my field, we don't have enough mathematics, but this course brings back my love for mathematics. Thank you very much!

автор: Carlos M V R

20 июня 2020 г.

It was a great course, but I suggest to be more clear with the information about the course (for example some people do not know anything about programming but it is necessary for finishing the course)

автор: SARA G C

3 авг. 2021 г.

El curso es descriptivo, simplificado, con ejemplos y ejercicios prácticos que promueven el aprendizaje y la adquisición de habilidades para el análisis de datos

автор: Magnus S

31 июля 2020 г.

Very informative and practical. Especially enjoyed learning the theory and Python practical in chunks and then bringing them together for the final assignment.

автор: Subhodeep S

23 окт. 2020 г.

The course has helped me grasp some important topics. Thanks to all the professors, teachers, staffs and coordinators for making this course so interesting.

автор: Basavaraj S A

5 мая 2020 г.

It is a good course and quite informative. I request instructors to give some more details about programming assignment giving details about submission