Department Events
Data Mining with Python
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 | |||
DAC333 | 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
