Predictive Analytics
Source: https://www.dtu.dk/english/education/graduate/msc-programmes/business-analytics/specialization/predictive-analytics Parent: https://www.dtu.dk/english/education/graduate/msc-programmes/business-analytics
Predictive Analytics
The tools used by an engineer in Business Analytics, are often grouped in:
- Descriptive Analytics, which can answer the question “What has happened?”
- Predictive Analytics, that focus more on finding out “What will happen?”
- Prescriptive Analytics, where actions are taken and thus answers the question “What should we do?”
The MSc in Business Analytics builds upon this concept and offers two optional specialization, each allowing you to become a specialist in certain areas:
- Predictive Analytics
- Prescriptive Analytics
The specialization in Predictive Analytics will equip the students with advanced skills in predictive modelling. You can apply cutting-edge machine learning tools to solve complex problems, involving noisy or incomplete data.
Aside from the mandatory courses from the mandatory core competence courses, the specialization in Predictive Analytics requires you to select the core competence courses in the following matter.
Select both of the following courses:
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
| 42186 | Model-based machine learning | 5 | point | Spring F5B (Wed 13-17) |
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and at least two of the following courses
| 02417 | Time Series Analysis | 5 | point | Spring F4B (Fri 8-12) |
| 02443 | Stochastic Simulation | 5 | point | June |
| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
| 42180 | Quantitative modelling of behaviour | 5 | point | Spring F3A (Tues 8-12) |
| 42417 | Simulation in Operations Management | 5 | point | June |
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Example study plans
Autumn start
Polytechnical foundation
Programme specific courses
Thesis
Electives
1.Semester
42577\ Introduction to Business Analytics
5 point
42500\ Innovation in Engineering (Polytechnical... Innovation in Engineering (Polytechnical Foundation)
5 point
12106\ Quantitative methods to assess... Quantitative methods to assess sustainability (Polytechnical Foundation)
5 point
Electives I \ Electives
15 point
2.Semester
42576\ From Analytics to Action
5 point
42578\ Advanced Business Analytics
5 point
42186\ Model-based machine learning
5 point
02417\ Time Series Analysis
5 point
02443\ Stochastic Simulation
5 point
42137\ Optimization using metaheuristics
5 point
3.Semester
02456\ Deep learning
5 point
02427\ Advanced Time Series Analysis
10 point
Electives II \ Electives
15 point
4.Semester
Thesis \ Thesis
30 point
\
Spring start
Spring start is a bit more complex, as most introductory courses will only be available on the second semester. The following study plan is an example of how a to follow the Predictive Analytics study line with winter start.
Polytechnical foundation
Programme specific courses
Thesis
Electives
1.Semester
02417\ Time Series Analysis
5 point
42137\ Optimization using metaheuristics
5 point
02443\ Stochastic Simulation
5 point
42500\ Innovation in Engineering (Polytechnical... Innovation in Engineering (Polytechnical Foundation)
5 point
12100\ Quantitative methods to assess... Quantitative methods to assess sustainability (Polytechnical Foundation)
5 point
Electives I \ Electives
5 point
2.Semester
42577\ Introduction to Business Analytics
5 point
02427\ Advanced Time Series Analysis
10 point
Electives II \ Electives
15 point
3.Semester
42578\ Advanced Business Analytics
5 point
42576\ From Analytics to Action
5 point
42180\ Quantitative modelling of behaviour
5 point
42186\ Model-based machine learning
5 point
Electives III \ Electives
10 point
4.Semester
Thesis \ Thesis
30 point
\
Specializations are merely recommended ways of choosing the courses in the curriculum. Applicants are not admitted to a specialization but to the programme and it is possible to choose among all the courses in the curriculum following the directions given. However, if a specialization has been fulfilled the title of the specialization may be added to the diploma.