ISYS6623003 – PREDICTIVE ANALYTICS (2/2 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: LO1 – Explain the principal of predictive analytic concepts; LO2 – Summarise various approaches of predictive analytic; LO3 – Design predictive analytic implementation.

Topics:

1. Evaluation;
2. Data to Insights to Decisions;
3. Information Based Learning;
4. Multinominal Logistic Regression;
5. Quiz 1;
6. Deep Learning;
7. K-Means Cluster;
8. Case Study Customer Churn;
9. Linear Regression;
10. Predictive Analytics Use Cases;
11. Reinforcement Learning;
12. Probability Based Learning;
13. Naïve Bayes Classifier;
14. Unsupervised Learning;
15. Market Basket Analysis;
16. Review;
17. Data Exploration;
18. Forecasting with Moving Average;
19. Quiz 2; Advance Smoothing Models;
20. Binominal Logistic Regression;
21. Project Submission;
22. Forecasting with Time Series: Smoothing;
23. Similarity Based Learning;
24. Error Based Learning;
25. Machine Learning for Predictive Data Analytics.