DS403BKK
Masters Machine Learning
Faculty
Ivan Solomatin
Leading Engineer at Samsung R&D Institute Russia.
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
This course introduces students to the contemporary state of Machine Learning and Artificial Intelligence. It combines the theoretical foundations of Machine Learning algorithms with extensive practical assignments. The curriculum spans classical algorithms through to Deep Learning approaches and recent advances in Artificial Intelligence.
Programming assignments will be completed in Python 3, with the PyTorch framework used for Deep Learning practice.
Special acknowledgement is given to Radoslav Neychev for his inspiration and for authoring most of the materials in this course.
Learning highlights
- Learn or remember basic ML algorithms and theoretical background.
- Learn unsupervised Learning techniques.
- Learn or remember the basics of Deep Learning.
- Learn techniques of DL-based image generation.
- Learn techniques of DL models optimisation and deployment.
- Get experience and intuition in solving ML and DL tasks in real applications.
Course outline
15 classes
Session 1
Intro: K-Nearest Neighbors (KNN), Naive Bayes.
Session 2
Linear Regression & Classification.
Session 3
Support Vector Machines (SVM) & Principal Component Analysis (PCA).
Session 4
Trees, Ensembles, and Gradient Boosting.
Session 5
Unsupervised Learning: Clustering, Dimensionality Reduction, etc.
Session 6
Introduction to Deep Learning & PyTorch.
Session 7
Neural Network Regularisation.
Session 8
CNNs and Image Processing.
Session 9
Unsupervised Deep Learning: VAE, C-VAE.
Session 10
Overview of problems in modern Computer Vision.
Session 11
Generative Models Overview: GANs, Diffusion Models, etc.
Session 12
DL Model Optimisation: Quantisation, Pruning, Distillation.
Session 13
DL Model Deployment Techniques Overview.
Session 14
Course Review and Exam Preparation.
Session 15
Final Exam.
Prerequisites
Basic python programming.
Basic calculus understanding.
Linear algebra.
Probability theory.
Methodology
The course will be organised in three-hour sessions and self-study practical assignments. Sessions will contain both theoretical and practical parts with different ratios depending on the materials.
Grading
Ivan Solomatin is an Expert Engineer at Samsung Research. His research interests are Biometrics, Computer Vision and Deep Learning. Received Bachelor (2016), Masters (2018) and PhD (2022) degree in Applied Mathematics at MIPT.
He was a coach for competitive programming for schoolchildren in 2016-2018. Since 2020 he has been teaching Algorithms at MIPT. Loves to communicate with students and tries to do his best to give them fast and efficient feedback.
See full profileApply for this course
Masters Machine Learning
by Ivan Solomatin
Total hours
45 Hours
Dates
Sep 29 - Oct 17, 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.