Section outline

  • Dear Learners,
    Wel-Come to the Course on Data Mining & Warehousing.It has Following Course Objectives
    & Course Outcomes:
    Prerequisites: Database Management System

    Course Objectives: 

    1. To understand the fundamentals of Data Mining.
    2. To identify the appropriateness and need of mining the data.
    3. To learn the pre-processing, mining and post processing of the data.
    4. To understand various Distant Measures techniques in data mining.
    5.  To understand clustering techniques and algorithms in data mining.
    6.  To understand classification techniques and algorithms in data mining

    Course Outcomes (COs): At the end of this course, students will be able to, 

    CO No.

    Title

    Bloom’s Taxonomy

    Level

    Descriptor

    CO1

    Understand basic, intermediate and advanced techniques to mine the data.

    2

     Understand

    CO2

    Apply the pre-processing techniques on data

    3

    Apply

    CO3

    Ability to explore the data warehouse and its design.

    4

    Analyze

    CO4

    Examine the hidden patterns in the data

    4

    Analyze

    CO5

    Apply the mining process by frequent pattern analysis techniques.

    3

    Apply

    CO6

    Demonstrate the Classification techniques for realistic data.

    3

    Apply

     

    Text Books:

    Sr. No.

    Authors

    Title

    Edition

    Year

    Publication

    1

    Han, Jiawei Kamber, Micheline Pei and Jian

    “Data Mining: Concepts and Techniques”,

     

     

    Elsevier Publishers

    2

    Mohammed J. Zaki, Wagner Meira Jr.

    “Data Mining and Analysis”

     

     

    Cambridge University Press,

     

    References Books:

    Sr. No.

    Authors

    Title

    Edition

    Year

    Publication

    1

    Vipin Kumar,

    “Introduction to Data Mining”,

     

     

    Pearson

    2

    Ikhvinder Singh,

    “Data Mining & Warehousing”,

     

     

    Khanna Publishing House

    3

    Charu C. Aggarwal

    “Data Mining: The Textbook”

     

     

    Springer

    4

    Ian H. Witten, Eibe Frank,

    “Data Mining: Practical Machine Learning Tool and Techniques”

     

     

    Elsevier Publishers

    5

    Luís Torgo,

    “Data Mining with R, Learning with Case Studies”

     

     

    CRC Press, Talay and Francis Group

    6

    Carlo Vercellis,

    “Business Intelligence - Data Mining and Optimization for Decision Making”

     

     

    Wiley Publications

     

    E-Resources:

     

    Thanks & Regards,
    Dr. T.Bhaskar
    Associate Professor(Computer Engg),Sanjivani College of Engineering,Kopragon
    Google-Site: https://sites.google.com/view/bhaskart/ug-notes/datamining-warehousing
    Moodle-Site: https://proftbhaskar.gnomio.com/course/view.php?id=3 (Log in as Guest)
    DMW YouTube Playlist: https://tinyurl.com/DMW-Bhaskar