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Master's Program in Statistics and Machine Learning at Linköping University

Linköping University Statistics Machine Learning Data Science

The Master's Program in Statistics and Machine Learning runs for two years and covers 120 ECTS credits, including a master's thesis.

Program Structure

Year 1: Core Courses

The first semester introduces essential courses in statistics, machine learning, and programming, laying a strong foundation for the rest of the program. Core courses include:

  • Statistical Methods
  • Machine Learning
  • Computational Statistics
  • Advanced Data Mining
  • Deep Learning
  • Big Data Analytics
  • Bayesian Learning

These courses form the backbone of the program, equipping students with critical knowledge and skills in statistics and machine learning.

Year 2: Profile and Elective Courses

During the third semester, students can choose from a range of profile courses designed to enhance their statistical and analytical expertise. Additionally, complementary courses allow students to specialize in applied fields or pursue interdisciplinary topics. Exchange study opportunities are also available in this semester.

Master's Thesis

To obtain the master's degree, students must complete:

  • 90 ECTS credits from coursework
  • 30 ECTS credits from a successfully defended master's thesis

The program aims to develop skilled professionals with a strong grasp of statistical analysis, machine learning, and applied data science techniques.

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Courses and Activities Completed During the Master's Program in Statistics and Machine Learning at Linköping University

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