Decision Support Systems (Data Science)
Course code
QUANT511
Course type
MSc Course
Weekly Hours
2,5
ECTS
5
Term
HS 2021
Language
Englisch
Lecturers
Juniorprof. Dr. Irina Heimbach
Please note that exchange students obtain a higher number of credits in the BSc-program at WHU than listed here. For further information please contact directly the International Relations Office.
Course content
- Simon’s model of decision making
- Introduction to DSS
- DSS and related concepts
- Introduction to data science
- Introduction to data science
- Recap data, statistical modeling, and visualization
- Logistic regression
- Decision trees
- Single perceptron
- Introduction to ANN, deep learning and cognitive computing
- Further predictive analytics models
- Practice with RapidMiner
- Text mining, sentiment analysis
- Social analytics
- Expert systems and recommenders
- Chatbots, virtual personal assistants, and robo-advisors
- Implementing DSS
- Legal, privacy, and ethics issues
- Impact on organizations, jobs, and works
- Technology trends and future of DSS
Class dates
Date | Time |
---|---|
Monday, 25.10.2021 | 08:00 - 11:15 |
Friday, 29.10.2021 | 08:00 - 11:15 |
Tuesday, 02.11.2021 | 08:00 - 11:15 |
Thursday, 11.11.2021 | 08:00 - 11:15 |
Friday, 12.11.2021 | 08:00 - 11:15 |
Tuesday, 23.11.2021 | 08:00 - 11:15 |
Friday, 26.11.2021 | 08:00 - 11:15 |
Friday, 03.12.2021 | 08:00 - 11:15 |
Tuesday, 14.12.2021 | 14:00 - 15:30 |
Learning outcomes
Improved data literacy and data-analytic skills
Improved working skills with RapidMiner
Understanding of main concepts of technology-mediated decision support
Literature
Sharda et al. 2021 Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th edition, Pearson.
Learningmethods
Lecture
Integrated exercises
Practice with a software (RapidMiner) and data sets
Quizzes
Group work, discussions
Exam
Project presentations (50%)
Final exam (50%)
Total workload
150