AD3411 DATA SCIENCE AND ANALYTICS LABORATORY Anna University Syllabus R2021
AD3411 DATA SCIENCE AND ANALYTICS LABORATORY L T P C
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OBJECTIVES:
- To develop data analytic code in python
- To be able to use python libraries for handling data
- To develop analytical applications using python
- To perform data visualization using plots
LIST OF EXPERIMENTS
Tools: Python, Numpy, Scipy, Matplotlib, Pandas, statmodels, seaborn, plotly, bokeh
Working with Numpy arrays
1. Working with Pandas data frames
2. Basic plots using Matplotlib
3. Frequency distributions, Averages, Variability
4. Normal curves, Correlation and scatter plots, Correlation coefficient
5. Regression
6. Z-test
7. T-test
8. ANOVA
9. Building and validating linear models
10. Building and validating logistic models
11. Time series analysis
PRACTICALS 60 PERIODS
OUTCOMES:
Upon successful completion of this course, students will be able to:
CO1. Write python programs to handle data using Numpy and Pandas
CO2. Perform descriptive analytics
CO3. Perform data exploration using Matplotlib
CO4. Perform inferential data analytics
CO5. Build models of predictive analytics
REFERENCES
1. Jake VanderPlas, “Python Data Science Handbook”, O’Reilly, 2016.
2. Allen B. Downey, “Think Stats: Exploratory Data Analysis in Python”, Green Tea Press,
2014.
3. Data Analysis and Visualization Using Python, Analyze Data to Create Visualizations for
BI Systems — Dr. Ossama Embarak
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