Data Mining with Python

Paper Code: 
BAC 333
Credits: 
4
Contact Hours: 
2.00
Max. Marks: 
100.00
Objective: 

The course will enable the students to

1. To study and learn the data science libraries for data analysis process

2. To develop their skills on python for data analysis on large data using R 

3. To understand the big data concept and data visualization.

 

Course

Learning outcome (at course level)

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

BAC333

Data Mining with Python

Students will:

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

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
Academic Year: 
2021-2022
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