DS205
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
The first part of the course provides an introduction to combinatorics and probability theory by uncovering their basic notions and techniques. We will learn how to compute the probability of an event and discuss standard probability distributions and their properties.
Then, we will move to statistical inference. Topics covered in this part of the course include point estimates, confidence intervals and hypothesis testing. In the last part of the course, we will learn to model the relationship between several variables with linear regression.
Since statistical analysis is typically done on the computer, homework will include not only pen-and-paper exercises but also practical assignments with Python.
Learning highlights
- The main goal of this course is to get familiar with the fundamental concepts of probability theory, as well as to learn how to perform and correctly interpret the results of statistical analysis.
Course outline
15 classes
Session 1
Combinatorics
Basic counting principles. Permutations and combinations.
Session 2
Probability of an Event
Session 3
Conditional Probability
Bayes’ Rule, Independent Events
Session 4
Discrete Random Variables 1
Probability distribution of a discrete random variable. Expected Value and Variance. Standard discrete distributions and their properties
Session 5
Discrete Random Variables 2
Joint distribution. (In)dependent random variables
Session 6
Continuous random variables 1
Density of distribution. Standard continuous distributions and their properties
Session 7
Continuous random variables 2
More on Normal distribution
Review
Session 8
Interim exam
Session 9
Descriptive vs Inferential statistics. Point estimation
Sampling distributions. The goal of inferential statistics. Estimators. Properties of estimators. Maximum Likelihood estimators.
Session 10
Interval estimation
Confidence interval. Examples of constructing confidence intervals for parameters of various distributions.
Session 11
Hypothesis testing
Introduction to hypothesis testing. Type I and II errors. alpha-level, p-value. Tests for the mean with known and unknown variances: one-sample Gauss test, one-sample t-test.
Session 12
Two-sample tests
Comparing the means of two independent samples with known and unknown variances: two-sample Gauss test, two-sample t-test. Comparing the means of two dependent samples: paired t-test.
Session 13
Linear Regression
Linear model. Method of Least Squares. Properties of the Linear Regression line. The goodness of fit.
Session 14
Review
Session 15
Final exam
Prerequisites
Basic Calculus and Linear Algebra, familiarity with Python is a plus.
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.
In order to further improve understanding of the taught material, ungraded tests and quizzes will be given regularly. Besides, graded homework will be assigned that will contribute to the final grade for the course.
There will be an interim exam in the middle of the course, followed by the final exam on the last 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
Probability & Statistics
by Evgeniya Korneva
Total hours
45 Hours
Dates
Jan 09 - Jan 27, 2023
Fee for single course
€1500
Fee for degree students
€750
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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.