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