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Applied Machine Learning

Master's level | 7.5 credits | Course code: DIT866
Spring 2020
50% Day
Göteborg
Period: 20 January 2020 - 21 March 2020
INSTRUCTION LANGUAGE: English
2 Opens 16 September GU-28665
2) Only EU/EEA citizens and students with approved residence permit in Sweden can apply

About the Course

The course gives an introduction to machine learning techniques and theory, with a focus on its use in practical applications. During the course, a selection of topics will be covered in supervised learning, such as linear models for regression and classification, or nonlinear models such as neural networks, and in unsupervised learning such as clustering.

The use cases and limitations of these algorithms will be discussed, and their implementation will be investigated in programming assignments. Methodological questions pertaining to the evaluation of machine learning systems will also be discussed, as well as some of the ethical questions that can arise when applying machine learning technologies.

There will be a strong emphasis on the real-world context in which machine learning systems are used. The use of machine learning components in practical applications will be exemplified, and realistic scenarios will be studied in application areas such as ecommerce, business intelligence, natural language processing, image processing, and bioinformatics. The importance of the design and selection of features, and their reliability, will be discussed.

More Information

https://gul.gu.se/public/cou...

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Course Syllabus

DIT866

Requirements and Selection

Requirements: To be eligible to the course, the student should have a Bachelor's degree in any subject, or have successfully completed 90 credits of studies in computer science, software engineering, or equivalent. Specifically, the course requires

  • at least 15 credits of successfully completed courses in programming,
  • one of the courses DIT851 Introduction to Data Science, 7.5 credits, or DIT855 Applied Mathematical Thinking, 7.5 credits, alternatively at least 7.5 credits of mathematics,
  • the course DIT861 Statistical Methods for Data Science, 7.5 credits, or at least 7.5 credits of probability theory, statistics, or mathematical statistics (e.g. MSG810 Mathematical Statistics and Discrete mathematics).

Selection: Selection is based upon the number of credits from previous university studies, maximum 225 credits.

Tuition Fee

Application fee: 900 SEK
Full course cost: 17 587 SEK
First payment: 17 587 SEK

EU/EEA citizens, Swedish residence permit holders and exchange students do not pay fees. More information on: http://www.universityadmissions.se

Study Guidance

E-post: svl@cse.gu.se

Department

Department of Computer Science and Engineering
41296 Göteborg

Visiting address: Rännvägen 6 B

Page Manager: Pontus Sundén
Last update: 6/15/2018 12:12 PM

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Page Manager: Pontus Sundén|Last update: 10/16/2018
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