Fall 2026: Data Mining-1

Logistics

• Class Timings: Mondays 10:30 am - 12:30 pm Thursdays 8:30 am - 9:30 am
• Classroom: Mondays (T-7) and Thursdays(T-11)
• Lab Timings: Mondays 1:30 pm - 3:30 pm
• Labs: Computer Lab 4 (CL-4)

Course Overview

• As per the Delhi University Course Syllabus/Guidelines

Lectures

Lecture	Topic	Lecture Slides	Readings
Unit-1	Introduction to Data Mining:	[unit1.pdf]	Chapter 1
Unit 2	Data Pre-Processing:	[unit2.pdf]	Chapter 2
Unit 3	Cluster Analysis:	[unit3.pdf]	Chapter 5
Unit 4	Association Rule Mining:	[unit4.pdf]	Chapter 4
Unit 5	Classification:	[unit5.pdf]	Chapter 3 & 6

Assignments and Tests

Class Assignments

• Assignment No. 1,
• Assignment No. 2,

Tests and Quizzes

• Test 1 :
• Test 2 :

Labs

Instructions

• Please be on time to avoid the Attendance Penalty.
• Please put your mobile phone on Silent Mode.
• Each lab assignment needs to be submitted in the Google Classroom for evaluation(will be notified in the GC lab-wise, submit before the deadline).
• Turn off(shut down) your assigned computer and arrange the chair before you leave the lab.

Lab 0: Getting Started ( week of 03^rd, 10^th & 17^th August 2026 )

Task No.	Task	Assessment Period.	Submission Deadline
1	https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial1/tutorial1.html	--	--
2	https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial2/tutorial2.html	--	--
3	https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial3/tutorial3.html	--	--

Lab 1: ( week of 24^th & 31^st August 2026 )

Task No.	Task	Assessment Period.	Submission Deadline
1	Apply data cleaning techniques on any dataset (e.g., Paper Reviews dataset in UCI repository). Techniques may include handling missing values, outliers and inconsistent values. A set of validation rules can be prepared based on the dataset and validations can be performed.	24/08/2026 - 31/08/2026	01/09/2026

Lab 2: ( week of 07^th & 14^th September 2026 )

Task No.	Task	Assessment Period.	Submission Deadline
2	Apply data pre-processing techniques such as standardization/normalization, transformation, aggregation, discretization/binarization, sampling etc. on any dataset	07/09/2026 - 14/09/2026	22/09/2025

Lab 3: ( week of 21^st & 28^th September 2026 )

Task No.	Task	Assessment Period.	Submission Deadline
5	Apply simple K-means algorithm for clustering any dataset. Compare the performance of clusters by varying the algorithm parameters. For a given set of parameters, plot a line graph depicting MSE obtained after each iteration.	21/09/2026 - 28/09/2026	29/09/2026

Resources

References:

• Text Book: Tan P.N., Steinbach M, Karpatne A. and Kumar V. Introduction to Data Mining, Second edition, Sixth Impression, Pearson, 2023.

Additional References:

1. Han J., Kamber M. and Pei J. Data Mining: Concepts and Techniques, 3rd edition, 2011, Morgan Kaufmann Publishers.
2. Zaki M. J. and Meira J. Jr. Data Mining and Machine Learning: Fundamental Concepts and Algorithms, 2nd edition, Cambridge University Press, 2020.
3. Aggarwal C. C. Data Mining: The Textbook, Springer, 2015
4. Insight into Data mining: Theory and Practice, Soman K. P., Diwakar Shyam, Ajay V., PHI 2006