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Statistical Methods for Data Science

Course
DIT862
Master’s level
7,5 credits (ECTS)
Study pace
50%
Time
Day
Location
Göteborg
Study form
Campus
Language
English
Duration
-
Application open
-
Application code
GU-18663
Tuition
Full education cost: 18 250 SEK
First payment: 18 250 SEK

No fees are charged for EU and EEA citizens, Swedish residence permit holders and exchange students.

More information about tuition fees

Application closed

About

The course gives an introduction to the theory of probability and statistics, data analysis using descriptive statistics and data visualization, and applications of probabilistic modeling in data science.

In the course, the following broad areas will be covered;

  • data analysis including descriptive statistics and data visualization probability theory including basic probability calculations, random variables, distributions
  • statistical methods including point and interval estimates, hypothesis testing, regression
  • probabilistic models in data science applications, for instance, Naive Bayes classifiers and topic models for text or Hidden Markov Models for sequences

Prerequisites 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 the following: at least 15 credits of successfully completed courses in programming, one of the courses DIT851 Introduction to Data Science, 7.5 credits, or DIT856 Applied Mathematical Thinking, Master course, 7.5 credits, alternatively at least 7.5 credits of mathematics. Applicants must prove knowledge of English: English 6/English B or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

Selection

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

For admission to the summer 2021 and onward the following selection applies: selection is based upon the number of credits from previous university studies, maximum 165 credits.