Advanced Simulation and Prescriptive Analytics

5 credits

Course, Master's level, 1TS316

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 November 2026–17 January 2027
Language of instruction
English
Entry requirements

130 credits in science/engineering, including 5 credits in computer programming, 20 credits in mathematics, 5 credits in statistics and probability theory, and 5 credits at Master's level in Industrial Engineering and Management and/or Computer Science. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Application deadline
15 April 2026
Application code
UU-14614

Admitted or on the waiting list?

Registration period
19 October 2026–1 November 2026
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 November 2026–17 January 2027
Language of instruction
English
Entry requirements

130 credits in science/engineering, including 5 credits in computer programming, 20 credits in mathematics, 5 credits in statistics and probability theory, and 5 credits at Master's level in Industrial Engineering and Management and/or Computer Science. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
19 October 2026–1 November 2026
Information on registration from the department

About the course

Simulation is arguably the most effective tool for modelling the complexity and dynamics of real-world production/business/healthcare systems and evaluating their performances. When combined with various data analytic and machine learning algorithms, simulation can provide the genuinely predictive and prescriptive capabilities required to solve real-world problems in the industry. This course will equip you with the knowledge and skills of not only advanced simulation for complex system modelling but also how simulation can be combined with various machine learning technologies for the purposes of system optimisation and principles learning.

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