DS112
Intro to Probability & Statistics
Faculty
Evgeniya Korneva
Senior Data Scientist at Monster
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
This is an introductory course to probability theory, a branch of mathematics concerned with understanding and quantifying randomness and uncertainty. Probability is useful in various fields such as statistics, finance, medicine, computer science, etc.
The mathematical framework for probability is built around sets. Thus, in the first week of this course, we will review the basics of set theory and study some fundamental methods for counting the number of elements infinite sets.
Then, we will dive into the foundations of discrete probability theory. During weeks two and three, we will discuss different interpretations of probability, learn to compute the probability of an event, get familiar with some common probability distributions and explore joint distributions of several random variables.
Learning highlights
- Know how to compute the number of permutations and combinations
- Learn how to compute the probability of an event
- Be familiar with the notions of independent events and conditional probability
- Be able to apply Bayes’ rule
- Know how to compute the expected value and variance of a discrete random variable
Course outline
15 classes
Basic Counting
Basics of set theory. Multiplication and addition principles. The principle of exclusion-inclusion
Permutations and Combinations - I
Permutations. Permutations with repeated elements. Combinations without replacement
Permutations and Combinations - II
Binomial theorem. Combinations with replacement.
Pigeonhole principle
Pigeonhole principle. Permutations and combinations review
Probability of an event - I
Definition of probability. Axioms of probability. Computing probability of an event
Combinatorics exam
Combinatorics exam
Probability of an event - II
The principle of exclusion-inclusion. Geometrical approach to probability
Conditional probability
Definition of conditional probability. Total probability theorem. Bayes’ rule. The Monty Hall Problem
Independent events
Independence of events. (Conditional) probability review
Random variables - I
Definition of a random variable. Probability mass function (PMF). Cumulative distribution function (CDF). Expectation and variance.
Random variables - II
Functions of random variables, their expectation and variance. Common discrete distributions and their properties
Independence of two random variables
Joint PMF. Covariance. Expectation and variance of a sum of two random variables
Conditional distribution
Conditional PMF. Marginal PMF. Law of total expectation.
Discrete probability review
Discrete probability review
Discrete probability exam
Discrete probability exam
Prerequisites
Basic Mathematics
Familiarity with Python is a plus but not required.
Methodology
Each three-hour class is a mixture of a lecture, where the new material is presented, and a practical section, where problems related to the topic of the day are solved and discussed.
To further improve understanding of the taught material, tests and quizzes will be given regularly. Also, five graded homeworks will be assigned and will contribute to the final grade for the course.
There will be two interim exams at the end of the first two weeks, followed by the final exam on the final day of the course.
Grading
Evgeniya was born in Moscow and got a bachelor’s degree in Applied Mathematics and Informatics from Higher School of Economics in 2015. She then moved to Belgium to continue her education at KU Leuven, where she got a master's degree in Artificial Intelligence. In October 2016, Evgeniya joined the DTAI research group as a doctoral researcher.
Apart from conducting research on Machine Learning, Evgeniya was teaching master’s courses on Fundamentals of AI and Data Mining. For three years in a row, she won The Best Teaching Assistant prize. Apart from that, Evgeniya volunteers as an instructor at summer schools and workshops, as well as creates educational content on programming and Machine Learning for several on-line learning platforms.
See full profileApply for this course
Intro to Probability & Statistics
by Evgeniya Korneva
Total hours
45 Hours
Dates
Jun 08 - Jun 26, 2026
Fee for single course
€1500
Fee for degree students
€750
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.