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Bachelor’s Programme 'Pure and Applied Mathematics'
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HSE Campus in Nizhny Novgorod

Bachelor’s Programme 'Pure and Applied Mathematics'

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Academic Supervisor
Nozdrinova, Elena
Manager
Nikolaeva, Yulia

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Computation and optimization for machine learning

2025/2026
Academic Year
ENG
Instruction in English
Delivered at:
Department of Fundamental Mathematics (Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod))
Course type:
Compulsory course
When:
4 year, 3 module

Instructor


Shubin, Danila

Course Syllabus

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Abstract

Course starts with a basic introduction to concepts concerning functional mappings. Later students are assumed to study limits (in case of sequences, single- and multivariate functions), differentiability (once again starting from single variable up to multiple cases), integration, thus sequentially building up a base for the basic optimisation. To provide an understanding of the practical skills set being taught, the course introduces the final programming project considering the usage of optimisation routine in machine learning.Additional materials provided during the course include interactive plots in GeoGebra environment used during lectures, bonus reading materials with more general methods and more complicated basis for discussed themes
HSE Campus in Nizhny Novgorod → Bachelor's programmes → Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod) → Bachelor's Programme in Pure and Applied Mathematics → Courses → Computation and optimization for machine learning, 2025/26 Academic year
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