Combinatorics and Probability

This course is part of Introduction to Discrete Mathematics for Computer Science Specialization

Instructors: Владимир Подольский +1 more

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Skills you'll gain

  •   Probability
  •   Python Programming
  •   Combinatorics
  •   Computational Thinking
  •   Statistics
  •   Game Theory
  •   Algorithms
  •   Mathematical Modeling
  • There are 6 modules in this course

    In this online 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.

    Binomial Coefficients

    Advanced Counting

    Probability

    Random Variables

    Project: Dice Games

    Explore more from Algorithms

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