�DSE3�BHCS17B�Introduction to Data Mining�Dr. Sarabjeet Kaur

Objective

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This course intends to make students learn about data mining techniques and apply the

techniques on real-life datasets available from various sources. The students will learn to

pre-process the dataset and make it suitable for data mining techniques. The course will

focus on three main techniques of data mining i.e. Classification, Clustering and

Association Rule Mining. Different algorithms for these techniques will be discussed.

Various evaluation metrics to judge the performance of the result will be discussed.

Learning Outcomes

On successful completion of the course, students will be able to do following:

• learn basics of data mining and its applications in real world.
• Get insight into the real-life data downloaded from various sources.
• Pre-process the data, and perform cleaning and transformation.
• Apply different classification algorithms, prepare the classifier and evaluate the performance of the classifiers based on various interestingness measures.
• Apply various clustering algorithms and evaluate the performance of clusters on the basis of various parameters.
• Use association rule mining algorithms on some datasets and generate frequent itemsets and association rules.

INTRODUCTION TO DATA MINING, 2ND EDITION TAN, STEINBACH, KARPATNE, KUMAR

5

Predictive Modeling

Clustering

Association �Rules

Milk

Data

Data Mining Course at a Glance (Learning Outcomes)

Data Quality & Preprocessing

Any Questions?