PM407
Product Analytics Fundamentals
Faculty
Alena Sludnova
Data analyst, Yango
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
During this course, students will learn about main elements used by product analysts on a daily basis. Course covers such topics as: applied statistics, AB-testing, data visualization & understanding. They will learn how to use Python and visualization tools to answer questions and present results.
Learning highlights
- Understand the data using statistics and visualization
- Use data insights to make decisions
- Design and conduct experiments
- Define key metrics for product and prioritize them
Course outline
15 classes
Session 1
Snow Summit
Introduction
Product analytics - why & how. Product metrics - how to choose and calculate.
Product metrics
Deep dive into product metrics and their hierarchy. 'Slow' and 'fast', user and business metrics.
Visualization p.1
Types of visualization, how to choose an appropriate plot. Introduction to visualization tools.
Visualization p.2
Learn more about visualization, practice with visualization tools.
SQL p.1
SQL syntax overview. Learn about selecting and grouping data. Practice with queries.
SQL p.2
Learn more about SQL (subqueries, window functions). Practice with queries.
Statistics p.1
Descriptive statistics. Measures of central tendency, data spread, distribution shape. How to use Python to calculate statistics.
Statistics p.2
Learn about hypothesis testing, correlation, statistical significance. Overview of main statistical tests. Use Python to implement tests on data samples.
A/B testing p.1
What is A/B testing and how to design basic experiments. How to analyze results.
A/B testing p.2
What are network effects and how to deal with them. Advanced A/B testing techniques.
User segmentation
Why and how to segment users. RFM overview. Clustering techniques. Use Python to clusterize users.
Cohort analysis
Why to split users into cohorts and what metrics to check. Pros and cons of cohort analysis. Perform basic cohort analysis using Python.
Course summary + cases
Review all topics, discuss cases to consolidate knowledge and prepare for the final project.
Final project
Solve case using acquired skills and present the result.
Prerequisites
Nice to have (not mandatory):
Basic Python programming skills
Basic statistics understanding
Methodology
Lectures, workshops, group projects, individual work.
Grading
Alena is a data specialist with 5+ years of experience, currently working at Yango, the international ride-hail company.
She is trying to combine both product and tech perspectives in her work, so she is always eager to understand users' pain and find quick and reliable solutions.
See full profileApply for this course
Product Analytics Fundamentals
by Alena Sludnova
Total hours
42 Hours
Dates
Feb 04 - Feb 21, 2025
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.