DATA MINING WITH PYTHON

Paper Code: 
DAC 333
Credits: 
4
Periods/week: 
60
Max. Marks: 
100.00
Objective: 

This paper will be based on theory paper DAC 331.Students will be able to apply and practice the concepts of Data mining.

 

Course Outcomes (COs):

   Course outcome (at course level)

Learning and teaching strategies

Assessment Strategies

 

 

 

Students will be able to:

CO11. Apply python libraries like pandas to create data frames for managing data

CO12. Implement data mining techniques using scikit libraries and other related libraries of python

CO13. Create visualizations using matplotlib library

CO14. Evaluate results generated using Python libraries

CO15. Generate a report based on analysis drawn from data mining techniques

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.

 

Assessment Strategies

Class test, Semester end examinations, Quiz, Practical Assignments, Individual and group projects

 

The practical covers the following topics:

·         Review of Python

·         Overview of Python tools for Data Analysis

·         Python has for data cleaning and processing -- pandas

·         Data exploration & analysis libraries for Data Science:Pandas, Numpy

·         Open-source software for mathematics, science, and engineering:SciPy

·         Data visualization/ plotting library: Matplotlib

·         Machine learning library: scikit-learn

 

 

ESSENTIAL READINGS: 

E-RESOURCES:

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

 

      JOURNALS:

  1. Journal of the Brazilian Computer Society, SpringerOpen
  2. Journal of Internet Services and Applications, SpringerOpen

 

Academic Year: 
2022-23
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