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== Level == Grundläggande nivå - First cycle course == Short description == Data appears in large volumes in several business applications. Analysing and making sense out of this data is crucial. This course provides the theoretical background as well as hands-on experience on how to apply different knowledge discovery and decision making in several sectors of business intelligence, such as financial data series modelling and customer behaviour analysis. == Aim == After completing this course the student should be able to: |
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== Aim == The course is intended for students who are interested in the theory and application of business intelligence methods and decision support systems. The course will include the basic theoretical backgrounds and several interesting real-world applications of data mining and decision support tools that can be used in business. The course will also discuss several artificial intelligence methods that play important roles in business applications. They include: * neural networks, * machine learning, * rule-based systems, * fuzzy logic, and * approximate reasoning. During the course the students are expected to learn the fundamentals of basic business intelligence methods and decision support techniques, and apply that knowledge in practice by solving some simple problems. The course does not build on any previous knowledge, however, the students are assumed to have an interest in practical problem solving. |
* explain the basic concepts and methods in business intelligence and the areas of decision support, data mining and artificial intelligence that can be used in business, * explain the characteristics of and relationships between the basic concepts of business intelligence and the areas of decision support, data mining and artificial intelligence that can be used in business, * see how simple problems can be modeled and solved using methods from the decision support, data mining and business intelligence relevant areas, * apply the methods of decision support, data mining and business intelligence to relevant areas. |
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Focusing on the area of business intelligence and decision support, the course will discuss the following topics: | The course is intended for students who are interested in theoretical and practical aspects of business intelligence and decision support systems. The course includes the basic theoretical background and some interesting applications of data mining and decision support tool that can be used in business. |
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* modeling, * optimization, * simulation, * data mining, and * decision support systems. |
With a focus on business intelligence and decision support the subjects to be covered in the course include: * Business modelling * The Cross-Industry Standard Process for Business Analytics * Decision support systems and decision making * Data mining: predictive and descriptive modeling * Model evaluation * Time series * Game theory for business * Social media |
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The course will be given in English. The course consists of lectures and practices. Participation is recorded on both lectures and practices, and active participation is highly rewarded. There will be regular (weekly) assignments that the students have to return on time. The course ends with a written exam. <<FullSearchCached(category:BI)>> ---- CategoryCategory |
The course is given as a distance course. |
BI - Business Intelligence
Level
Grundläggande nivå - First cycle course
Short description
Data appears in large volumes in several business applications. Analysing and making sense out of this data is crucial. This course provides the theoretical background as well as hands-on experience on how to apply different knowledge discovery and decision making in several sectors of business intelligence, such as financial data series modelling and customer behaviour analysis.
Aim
After completing this course the student should be able to:
- explain the basic concepts and methods in business intelligence and the areas of decision support, data mining and artificial intelligence that can be used in business,
- explain the characteristics of and relationships between the basic concepts of business intelligence and the areas of decision support, data mining and artificial intelligence that can be used in business,
- see how simple problems can be modeled and solved using methods from the decision support, data mining and business intelligence relevant areas,
- apply the methods of decision support, data mining and business intelligence to relevant areas.
Syllabus
The course is intended for students who are interested in theoretical and practical aspects of business intelligence and decision support systems. The course includes the basic theoretical background and some interesting applications of data mining and decision support tool that can be used in business.
With a focus on business intelligence and decision support the subjects to be covered in the course include:
- Business modelling
- The Cross-Industry Standard Process for Business Analytics
- Decision support systems and decision making
- Data mining: predictive and descriptive modeling
- Model evaluation
- Time series
- Game theory for business
- Social media
Outline
The course is given as a distance course.