Data Mining with Python

Paper Code: 
DAC 333
Credits: 
04
Periods/week: 
02
Max. Marks: 
100.00
Objective: 

Learning outcome (at course level)

Learning and teaching strategiesAssessment Strategies
   

Students will be able to:

  1. Explain and apply python data science libraries as a tool for data analytics
  2. Implement Python codes for the various data mining techniques
  3. Create visualizations using python
  4. Evaluate widely used Python packages used for Data Analysis and Data Visualization projects.

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: 
2020-21
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