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University of Gothenburg

Advanced machine learning with neural networks

This course introduces students to recent developments and state-of-the-art methods in machine learning using artificial neural networks. This advanced course builds on Machine learning with neural networks (FFR135) and provides an in-depth analysis of many of the concepts and algorithms that were briefly introduced…

  • Higher education
  • Information unavailable
  • 23 March 2026
  • Information unavailable
  • Information unavailable
  • 50 %

Overview

This course introduces students to recent developments and state-of-the-art methods in machine learning using artificial neural networks. This advanced course builds on Machine learning with neural networks (FFR135) and provides an in-depth analysis of many of the concepts and algorithms that were briefly introduced in that course, with particular emphasis on applications in the natural and engineering sciences. The goal is to become familiar with several advanced machine-learning methods, and to code them efficiently in Python using current neural-network packages. An essential part of the course are projects in deep learning and reinforcement learning.

Admission scores

Uppgift saknasVerified data is not connected to this education offering.

Entry requirements

A Bachelor's degree in physics, mathematics, computer science, or similar including 30 credits of mathematics.Applicants must prove their knowledge of English: English 6/English B from Swedish Upper Secondary School or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.

Source, measure and data quality
Source
Skolverket Susa-navet
Period
2026-03-23
Measure
Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
Population
Education offering e.uoh.gu.fym360.11053.20261
Last checked
2026-09-23T10:36:47.551594+00:00
Limitation
Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.

Programme content

Uppgift saknasVerified data is not connected to this education offering.

Study structure

Uppgift saknasVerified data is not connected to this education offering.

Application and important dates

  1. Programme or course starts
  2. Programme or course ends

Salary and salary distribution

Uppgift saknasVerified data is not connected to this education offering.

Common occupations after graduation

Uppgift saknasVerified data is not connected to this education offering.

Students

Uppgift saknasVerified data is not connected to this education offering.

Geographical background

Uppgift saknasVerified data is not connected to this education offering.

Previous upper-secondary schools and programmes

Uppgift saknasVerified data is not connected to this education offering.

Completion and outcomes

Uppgift saknasVerified data is not connected to this education offering.

About the provider

University of Gothenburg

Provider for the published education offering.

Sources and data quality

Education facts for the selected offering come from Skolverket Susa-navet.

Retrieved . Published . Times are shown in Swedish local time.

Source identity and publication version
Publication version
8e217193-f5fa-4778-b085-a4521fd03e8d
Education identity in the source
i.uoh.gu.fym360.11053.20261
Offering identity in the source
e.uoh.gu.fym360.11053.20261
Education-form source code
HS
Education code in the source
FYM360
Change time according to the source
2026-01-27T14:29:43

The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.