Retour à Combinatorics and Probability

4.6

268 notes

•

50 avis

Counting is one of the basic mathematically related tasks we encounter on a day to day basis. The main question here is the following. If we need to count something, can we do anything better than just counting all objects one by one? Do we need to create a list of all phone numbers to ensure that there are enough phone numbers for everyone? Is there a way to tell that our algorithm will run in a reasonable time before implementing and actually running it? All these questions are addressed by a mathematical field called Combinatorics.
In this course we discuss most standard combinatorial settings that can help to answer questions of this type. We will especially concentrate on developing the ability to distinguish these settings in real life and algorithmic problems. This will help the learner to actually implement new knowledge. Apart from that we will discuss recursive technique for counting that is important for algorithmic implementations.
One of the main `consumers’ of Combinatorics is Probability Theory. This area is connected with numerous sides of life, on one hand being an important concept in everyday life and on the other hand being an indispensable tool in such modern and important fields as Statistics and Machine Learning. In this course we will concentrate on providing the working knowledge of basics of probability and a good intuition in this area. The practice shows that such an intuition is not easy to develop.
In the end of the course we will create a program that successfully plays a tricky and very counterintuitive dice game.
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 IT, starting from motivated high school students.
Do you have technical problems? Write to us: coursera@hse.ru...

Aug 03, 2019

Had loads of fun during most part of the course. Frequent quizzes keep the learner on toes. Thoroughly enjoyed the final programming quiz to implement a dice game.

Oct 13, 2018

I really enjoyed taking this course. The teaching was pretty good and some of the quiz questions will challenge you if you haven't done Combinatorics before.

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par Charalampos R P

•Oct 09, 2018

Most of the courses of this specialisation (not only on prob) are VERY hard to follow. Instructors lack of passion while teaching and they just reading the script from the slides. Whatever I passed and learned was from random sources at the internet.

To the instructors: Take a blackboard and start solving the problems by hand. By reading a long queue of numbers from slides for 10min, the student can't follow at all. This is not a simple presentation, this is math topics. You can't just pass a slide full of numbers and some sentences thinking that the student can comprehend all that stuff.

On the other hand, on the 3rd party quizzes has been made a magnificent job.

par Vijay R

•Nov 24, 2018

While I imagine Alexander Shen to be a great person and a math genius, he seems entirely unprepared for the lectures. He speaks well, I can understand his accent, but his lack of preparation and poor slides make a difficult situation terrible. The other instructors do a much better job, but I also wish there were more tests of our knowledge.

par Mike P

•Mar 03, 2019

Quite enjoyable, however Alex is not the strongest presenter though his passion is evident :)

par Mallori H

•Oct 05, 2017

Hard to understand lecturer

par Serhat G

•Dec 22, 2018

Excellent, thanks.

par Ziqi Y

•Dec 31, 2018

Great! Challenging final project but worth trying!

par Miguel D

•Nov 26, 2018

Super interesting the topic about combinatorics

par Zhe Y

•Jul 23, 2018

pure math course...

par Saptarshi M

•Oct 10, 2018

Concepts are presented in such a way that a novice can understand easily. For an advanced learner, there are concepts that are lit from a different perspective. Not all the instructors are equally competent. Sometimes you have to watch the videos twice to get the full understanding. But that's worth of your time. Overall enjoyable. Programming practices are also good and of intermediate quality.

par Ziad B

•Oct 13, 2018

I really enjoyed taking this course. The teaching was pretty good and some of the quiz questions will challenge you if you haven't done Combinatorics before.

par Chen Z

•Sep 11, 2018

The final project is hard for me cuz I don't have Python experience. and the logic is a little bit complicated. That's not for absolutely beginners!

par AJ A

•Sep 26, 2018

Good first course in probability/combinatorics at the university level; last assignment had a lot more coding than other assignments, a lot more

par Ashish D S

•Jul 14, 2018

Content of this course is excellent. Basic Python programming skill is required for this course.

par HaotianWang

•Jul 15, 2018

useful

par Javier O

•Dec 15, 2017

Excellent and complete course. I completely recommend it

par Joseph A D

•Feb 11, 2018

informative material presented clearly and simply. I had studied bayes before and it was nice to get a concise review.

par Xiaoyuan C

•Jan 12, 2018

Excellent course! Thanks for the effort of the course team!

par Vamsee M K

•Dec 02, 2017

A very nice introduction to probability and combinatorics.

par Andrew M

•Nov 11, 2017

A great course that is well organized. I love Professor Alexander Shen, because he makes me happy.

par Ganna S

•Nov 22, 2017

Great!)

par Arka M

•Jul 08, 2018

Great Course.

par Dmytro N

•Nov 01, 2017

I like the course very much! Thanks a lot guys, keep creating new courses!

par Pedro M H V

•Jun 18, 2018

Really nice introduction to discrete math and basic algorithms. The content is quite basic, but as mentioned in the syllabus is for beginners. Still, for those of you who are at that level is worth taking this specialization.

par Stefan D

•Nov 18, 2017

Loved it

par liang t

•Jan 06, 2018

It is a pretty good course. although I have learnt probability theory both in undergraduate and postgraduate level, it still gives me some inspiration toward probability theory. I love the examples given in the lecture, which are classical and typical enough. Some paradoxes examples help me to understand the probability theory better and clearer.

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