DS404BKK
Machine Learning in Applications
Faculty
Evgenii Nazarov
Technical Lead / Senior Machine Learning Engineer at Yandex
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
Various methods of machine and deep learning are applied in the field of information retrieval, which encompasses recommender systems, ranking, and search. In this course, students will be introduced to both classical machine learning methods and modern neural network approaches, analyse real-life cases, and learn how to implement their results in production. The course places particular emphasis on cutting-edge solutions from leading technology companies, as well as business challenges students may encounter in the future.
Learning highlights
- Learn the theory and concepts of recommender system models, methods for their evaluation.
- Understand the scope of applicability of these models, their limitations and advantages.
- Gain experience with system design for various scenarios.
- Understanding of modern industry and current challenges.
- Ready to face real business challenges.
Course outline
15 classes
Session 1
Introduction and baselines.
Session 2
Gradient Boosting I.
Quality metrics & Evaluation.
Session 3
Gradient Boosting II.
Learning to Rank.
Session 4
Gradient Boosting III.
Feature Engineering & Calibration.
Session 5
Factorization Machines I.
Session 6
Factorization Machines II.
Session 7
Deep Learning Intro.
Session 8
Deep Learning for Ranking.
Session 9
Homework discussion.
Session 10
Deep Learning for Candidates Generation.
Session 11
Additional topics.
Session 12
Recommendations in production.
Online validation.
Session 13
Homework discussion.
Session 14
System Design.
Session 15
Final Exam.
Prerequisites
Basics of Python programming.
Basics of Machine Learning (understanding of Deep Learning will be a great plus).
Basics of Linear Algebra and Probability Theory.
Methodology
Each three-hour session will consist of a lecture and a seminar. Lectures will focus on presenting concepts, while seminars will focus on practical problem solving and teamwork. During the course there will be long-term homework assignments and a final exam. Also, during the course, some lessons will be devoted to discussions of homework solutions and Q&A sessions.
Grading
Software engineer with a strong background in developing and deploying machine/deep learning models in the field of ranking, search and pricing with 5+ years experience. Led the development of an advertising platform used by millions of people every month. Most of my experience has been gained in the e-commerce industry and in fast-growing startups. Taught advanced programming courses to school and university students.
See full profileApply for this course
Machine Learning in Applications
by Evgenii Nazarov
Total hours
45 Hours
Dates
Oct 20 - Nov 07, 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.