BUSINESS SIMULATION (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: LO1 – define of the concept of business analytics, simulation, and decision making; LO2 – explain of the probability theory and probability distribution as the basis of simulation and BI Tools for Data Analysis; LO3 – Use of the data as the basis of simulation and BI Tools for predictive and prescriptive analytical decision; LO4 – demonstrate of the tools for analyzing the data for decision making business strategy.

Topics:

1. Introduction to Data Analysis and Decision Making;
2. Overview Business Intelligence, Analytics, Data Science, and Artificial Intelligence: System for Decision Support;
3. Artificial Intelligence Concepts, Drivers, Major Technologies, and Business Applications;
4. Decision Making Under Uncertainty;
5. Machine-Learning Techniques for Predictive Analytics;
6. Nature of Data, Statistical Modeling and Visualization;
7. Business Intelligence (BI) Tools for Data Analysis;
8. Text Mining, Sentiment Analysis, and Social Analytics;
9. Prescriptive Analytics: Optimization and Simulation;
10. Big Data, Cloud Computing, and Location Analytics: Concepts and Tools;
11. Robotics: Industrial and Consumer Applications;
12. Group Decision Making, Collaborative Systems, and AI Support;
13. The internet of Things as a Platform for Intelligence Applications;
14. Presentation AoL Project and Case Study.
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