DS406
Statistical Data Analysis
Faculty
Timofey Vilkov
Senior Product Analyst at Manychat, Barcelona
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
This advanced course explores statistical methods with a strong focus on real-world applications. Students will work with data using Python, learn how to extract insights through visualisation and analysis, and understand the principles behind modern inference techniques. The course examines how statistical thinking supports experiments and decision-making, from classic tests to causal analysis. It combines theoretical foundations with practical tools, helping students develop an intuition for uncertainty, patterns, and evidence in data.
Learning highlights
- Learn how to recognise data analysis problems that require statistical thinking.
- Select appropriate methods to address them using real-world data and Python tools.
Course outline
15 classes
Introduction
Foundations of statistical science: distributions and statistics. Pandas & Numpy.
Exploratory Data Analysis
From visualisation to hidden paradoxes.
CLT and LLN
Asymptotic theory in practice: LLN and CLT.
Estimation and hypothesis tests
Point and interval parameter estimates. Fundamentals of hypothesis testing.
Parametric tests
Hypotheses about proportions, means, and variances.
Goodness-of-Fit Tests and the Magic of Bootstrap
K-S Test, Chi-Squared test and bootstrap.
Multiple hypothesis testing
Family-wise error rate, false discovery rate, and methods to control them.
Experimentation
The art and science of A/B testing.
Linear models
Statistical perspective on linear and logistic regression.
Snow Summit
Snow Summit (No Class)
Snow Summit
Snow Summit (No Class)
Foundations of causal thinking
Intro to DAGs and fighting confounding.
Classic effect estimation methods
Propensity Score Matching and Difference in differences.
Causal Inference & Machine Learning
Uplift modeling and Double ML.
Final exam
Final exam
Course materials
Books
Prerequisites
Probability and Statistics
Machine Learning
Methodology
Lectures, exercises, individual work.
Grading
Timofey Vilkov is a product analyst with expertise in A/B testing, causal inference, and user behavior analytics. He holds a Master’s degree in Computer Science from the Higher School of Economics. Over the past five years, Timofey has worked at Manychat, Avito, and Tinkoff, where he led data-driven product decisions. He also designed and wrote theoretical and practical materials for online education programs (Yandex Practicum), focusing on probability and statistics for data analysts and data scientists, and worked as a project reviewer.
See full profileApply for this course
Statistical Data Analysis
by Timofey Vilkov
Total hours
45 Hours
Dates
Jan 12 - Jan 30, 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.