INTRODUCTION TO DATA ANALYTICS (2 CREDITS)

Learning Outcomes:

On successful completion of this course, students will be able to: LO1 – explain data, tools and technology aspects in data analysis; LO2 – discuss model, method and process in descriptive analytics; LO3 – discuss popular data analytic application; LO4 – apply predictive analytic to support decision making.

Topics:

1. What Can We Do With Data?;
2. Descriptive Statistics;
3. Descriptive Multivariate Analysis;
4. Data Quality and Preprocessing;
5. Clustering; Frequent Pattern Mining;
6. Cheat Sheet and Project on Descriptive Analytics;
7. Regression;
8. Classification;
9. Additional Predictive Methods;
10. Advanced Predictive Topics;
11. Working with Texts;
12. Cheat Sheet and Project on Predictive Analytics.