People Innovation Excellence


Learning Outcomes:

On successful completion of this course, student will be able to: explain the motivations, concepts, methods, and methodologies for different types of analytics; recognize the new technology trends as the enablers of the modern-day analytics; analyze current applications of technology trends using several methodologies; identify current trends and issues in the analytical information system.


  1. Overview of Business Intelligence, Analytics, Data Science, and Artificial Intelligence: Systems for Decision Support
  2. Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Application
  3. Nature of Data, Statistical Modeling, and Visualization
  4. Data Mining Process, Methods, and Algorithms
  5. Machine-Learning Techniques for Predictive Analytics
  6. Deep Learning and Cognitive Computing
  7. Text Mining, Sentiment Analysis, and Social Analytics
  8. Prescriptive Analytics: Optimization and Simulation
  9. Big Data, Cloud Computing, and Location Analytics: Concept and Tools
  10. Robotics: Industrial and Consumer Applications
  11. Group Decision Making, Collaborative Systems, and AI Support
  12. Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors
  13. The Internet of Things as a Platform for Intelligent Applications
  14. Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts

Published at : Updated

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