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Home > Data Mining With Python

Data Mining With Python [1]

Paper Code: 
25DAC333
Credits: 
4
Periods/week: 
2
Max. Marks: 
100.00
Objective: 

This course will be based on theory paper DAC 331. This course will enable students to apply and practice the concepts of Data mining.

Course Outcomes: 

Learning outcome

(at course level)

Learning and teaching strategies

Assessment Strategies

  1. Apply python libraries like pandas to create data frames for managing data
  2. Implement data mining techniques using scikit libraries and other related libraries of python
  3. Create visualizations using matplotlib library
  4. Evaluate results generated using Python libraries
  5. Generate a report based on analysis drawn from data mining techniques
  6. Contribute effectively in course-specific interaction

Approach in teaching:

Interactive Lectures, Discussion, Demonstrations, Group activities, Teaching using advanced IT audio-video tools. 

Learning activities for the students:

Effective assignments, Giving tasks.

One Annual Practical Test, File/Seminar/Reports etc.

 

The practical covers the following topics:

  1. Review of Python
  2. Overview of Python tools for Data Analysis
  3. Python has for data cleaning and processing -- pandas
  4. Data exploration & analysis libraries for Data Science: Pandas, Numpy
  5. Open-source software for mathematics, science, and engineering: SciPy
  6. Data visualization/ plotting library: Matplotlib
  7. Machine learning library: scikit-learn [2]
ESSENTIAL READINGS: 
  1. Jiawei Han & Micheline Kamber, “Data Mining: Concepts & Techniques”, Morgan Kaufmann Publishers, Third Edition.
  2. Mohanty, Soumendra, “Data Warehousing: Design, Development and Best Practices”, Tata McGraw Hill, 2006
REFERENCES: 
  1. W. H. Inmon, “Building the Data Warehouse”, Wiley Dreamtech India Pvt. Ltd., 4th  Edition, 2005

 

e-Resources:

  1. https://www.slideshare.net/ [3]
  2. https://nptel.ac.in/courses/106106222 [4]
  3. https://spoken-tutorial.org/??/ [5]
  4. www.kaggle.com

 

Journals:

1.   Journal of the Brazilian Computer Society, SpringerOpen

2.   Journal of Internet Services and Applications, SpringerOpen

Academic Year: 
2025-26 [6]

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Source URL: https://www.csit.iisuniv.ac.in/courses/subjects/data-mining-python-4

Links:
[1] https://www.csit.iisuniv.ac.in/courses/subjects/data-mining-python-4
[2] http://scikit-learn.org/stable/
[3] https://www.slideshare.net/
[4] https://nptel.ac.in/courses/106106222
[5] https://spoken-tutorial.org/??/
[6] https://www.csit.iisuniv.ac.in/academic-year/2025-26