INTRODUCTION TO DATA ANALYTICS (BME456C)

INTRODUCTION TO DATA ANALYTICS

Course Code BME456C 
CIE Marks 50
Teaching Hours/Week (L:T:P: S) 0:0:2:0 
SEE Marks 50
Total Hours of Pedagogy 15 sessions 
Total Marks 100
Credits 01 
Exam Hours 03
Examination type (SEE) Practical

Experiments

1 Use Numpy to create single and multi-dimensional array and perform various operations using

Python.

2 Use Pandas to access dataset, cleaning, manipulate data and analyze using Python

3 Use matplot library to plot graph for data visualization using Python

4 Determine probability, sampling and sampling distribution using Python

5 Determine frequency distributions, variability, average, and standard deviation using Python

6 Draw normal curves, correlation, correlation coefficient and scatter plots using Python

7 Implement and analyze Linear regression in Python (Single variable & Multivariable)

8 Implement and analyze Logistic regression in Python

9 Implement and analyze Decision tree algorithm in Python

10 Implement and analyze Random Forest algorithm in Python

Only for CIE

11 Implementation of two samples T-test and paired two-sample T-test in excel.

12 Implementation of one-way and two-way ANOVA in excel.

Suggested Learning Resources:

• McKinney, W. (2012). Python for data analysis: Data wrangling with Pandas, NumPy, and

IPython. " O'Reilly Media, Inc.".

• Swaroop, C. H. (2003). A Byte of Python. Python Tutorial.

• Ken Black, sixth Editing. Business Statistics for Contemporary Decision Making. “John Wiley &

Sons, Inc”

• https://www.simplilearn.com/tutorials/data-analytics-tutorial/data-analytics-with-python

• https://www.youtube.com/watch?v=GPVsHO