Data Mining and Warehousing detailed syllabus for Cyber Forensics & Information Security (CF) for 2021 revision curriculum has been taken from the SITTTRs official website and presented for the Cyber Forensics & Information Security (CF) students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Cyber Forensics & Information Security 6th Sem scheme and its subjects, do visit Cyber Forensics & Information Security (CF) 6th Sem 2021 regulation scheme. For Open Elective-I scheme and its subjects refer to Cyber Forensics & Information Security (CF) Open Elective-I syllabus scheme. The detailed syllabus of data mining and warehousing is as follows.
Course Objectives:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
.
Course Outcomes:
On completion of the course, the student will be able to:
- Interpret the fundamental concepts of data mining and its applications
- Understand investigation of data for preprocessing using practical data mining tools Applying
- Understand Association Rules in data mining and need of clustering Applying
- Understand advanced Data Mining techniques Applying
Module 1:
Data Mining:- Concepts and Applications, Data Mining Stages, Data Mining Models, Data Warehousing (DWH) and On-Line Analytical Processing (OLAP), Need for Data Warehousing, Challenges, Application of Data Mining Principles, OLTP Vs DWH, Applications of DWH
Module 2:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Module 4:
Hierarchical Clustering method: BIRCH. Density-Based Clustering -DBSCAN and OPTICS. Advanced Data Mining Techniques: Introduction, Web Mining- Web Content Mining, Web Structure Mining, Web Usage Mining. Text Mining.
Graph mining:- Apriori based approach for mining frequent subgraphs. Social Network Analysis:- characteristics of social networks. Link mining:- Tasks and challenges.
Text Books:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
- Dunham M H, “Data Mining: Introductory and Advanced Topics”, Pearson Education, New Delhi, 2003.
- Jaiwei Han and Micheline Kamber, “Data Mining Concepts and Techniques”, Elsevier,2006.
Reference Books:
- Mehmed Kantardzic, “Data Mining Concepts, Methods and Algorithms”, John Wiley and Sons, USA, 2003.
- Pang-Ning Tan and Michael Steinbach, “Introduction to Data Mining”, Addison Wesley, 2006.
Online Resources
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
For detailed syllabus of all other subjects of Cyber Forensics & Information Security, 2021 revision curriculum do visit Cyber Forensics & Information Security (CF) 6th Sem subject syllabuses for 2021 revision.
To see the syllabus of all other branches of diploma 2021 revision curriculum do visit SITTTR diploma all branches syllabus..
To see the results of Cyber Forensics & Information Security of diploma 2021 revision curriculum do visit SITTTR diploma results..
For all Cyber Forensics & Information Security academic calendars, visit Cyber Forensics & Information Security all semesters academic calendar direct link.