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Data Mining

By Mr. L. Abraham David   |   St.John’s College, Palayamkottai
Learners enrolled: 5377
Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Data mining is the extraction of hidden predictive information from large databases is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. 

Data mining methodology extracts hidden predictive information from large databases. With such a broad definition, however, an online analytical processing (OLAP) product or a statistical package could qualify as a data mining tool. Retail companies and the financial community are using data mining to analyze data and recognize trends to increase their customer base, predict fluctuations in interest rates, stock prices, and customer demand.

Summary
Course Status : Ongoing
Course Type : Core
Duration : 12 weeks
Start Date : 10 Jun 2020
End Date : 30 Nov 2020
Exam Date :
Enrollment Ends : 30 Sep 2020
Category :
  • Computer Science and Engineering
Credit Points : 4
Level : Undergraduate

Page Visits



Course layout


Week – I 

1. Introduction to Data Mining
2. Introduction to Data Warehousing
3. OLAP
4. Trends in Data Warehousing

Week – II  

5. Applications in Data Warehousing
6. Data Warehousing Architecture-I
7. Data Warehousing Architecture-II
8. Data Warehousing Architecture-III

Week – III

9. Data Warehousing Architecture-IV
10.Data Warehousing Architecture-V 
11. Data Mining-I
12. Data Mining-II
     
Week – IV

13. Data Mining-III
14. Data Mining-IV
15. Data Mining-V
16. Data Mining-VI

Week – V

17. Data Mining-VII
18. Association Rule Mining-I
19. Association Rule Mining-II

Week – VI  

20. Association Rule Mining-III
21. Association Rule Mining-IV
22. Association Rule Mining-V

Week – VII  

23. Classification Techniques-I
24. Classification Techniques-II

Week – VIII

25. Classification Techniques-III
26. Classification Techniques-IV

Week – IX

27. Classification Techniques-V
28. Classification Techniques-VI

Week – X

29. Classification Techniques-VII

Week – XI
30. Other Data Mining Methods-I
31. Other Data Mining Methods-II

Week – XII
32. Other Data Mining Methods-III
33. Other Data Mining Methods-IV

Books and references

1. Jiawel Han and Micheline Kamber, “Data mining concepts and Techniques”
2. Berson, “Data Warehousing,Data Mining, OLAP”
3. Pang-Ning Tan,  Michael Steinbach, Vipin Kumar “ Introduction to Data Mining”
4. Arun K Pujari, “Data Mining Techniques”
5. Dunham M H, “Data Mining-Introductory and Advanced Topics”

Instructor bio





Mr. L. Abraham David

St.John’s College, Palayamkottai
Mr.Abraham David L has been associated  with Department Of Computer Application and M.Sc (NT & IT ), St.John’s college , Palayamkottai affiliated to M.S university Since 22nd  August 2014. He has conducted a several seminar in college. He has invited from various college to deliver a guest talk. He has published a journal and 2 national conference in research articles. He has attended many seminars and workshops. He presented a E-content for EMRC Furthermore, he is involved in developing Massive Open Online Course (MOOC) in SWAYAM Platform.

Course certificate

30% for in course Assessment & 70% of end term Proctored Exam


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