Data Science syllabus

MDM-271-INC · Second Year Instrumentation and Control Engineering, SPPU 2024 pattern. Every unit, the marks scheme, course outcomes and books, copied from the official syllabus PDF.

MDM-271-INC2 h/week theoryCCE 30 + End-sem 70

04.units

02.credits

Unit-wise syllabus

UNIT I

Data Science

5 hours

Data Science Life Cycle, Data Science Software Tools, Programming Languages for Data Science, Applications of Data Science, types of data. Data Collection and Sampling. Statistics: Descriptive Statistics: Measurement of central tendency (Mean, median and mode), measurement of spread (Range, IQR, variance, standard deviation), correlation, covariance and Inferential Statistics (Probability, Hypothesis testing).

UNIT II

Data Science Packages

8 hours

NumPy- Array Operation, Indexing//slicing, mathematical operations, Matrix operations, String operation. Pandas- Basic pandas’ operation on data frame, append, loc and iloc, missing values, merge, concat, join, group by, pivot, melt, date time index, Matplotlib- Histogram, Line chart, bar chart, pie chart, scatter plot, subplot, imshow. Seaborn- Histogram, line chart, pie chart, bar chart, scatter pot, heatmap, pair plot SciPy- used for scientific purpose SkLearn- used for Machine learning

UNIT III

Exploratory Data Analysis

6 hours

Identification of variables and data types, Univariate, bivariate, multivariate analysis, Variable transformations, Missing value treatment (Mean /median/mode methods) Outlier treatment (Percentile, Std dev, IQR, Boxplot, Z score).

UNIT IV

Data Cleaning and Data Visualization

7 hours

Categorical to Numerical: One hot encoding, dummies, Label encoding, Correlation Analysis, Feature Selection, Feature Rescaling (Normalization and Standardization ) Feature Transformation(Log, exponential, square ) Tableau Desktop: Different types of Databases, Connecting With Data, different types of charts, Creating Views and Analysis, case study.

Marks and credits

Head	Marks	Credit
CCE (continuous comprehensive evaluation)	30	2
End-semester exam	70	2

Prerequisite: Data Structure, Data Science Software Tools..

Course outcomes

CO1Execute data collection and sampling methods to gather data for analysis effectively.
CO2Implement statistical tools and techniques to analyze and interpret data accurately.
CO3Use data science packages for data processing, analysis, and visualization efficiently.
CO4Demonstrate proficiency in exploratory data analysis techniques and present insights effectively.

Books

Text books

Python for data analysis by O’Reilly
Data Visualization in python by Daniel Nelson
Mastering Python for Data Science by Samir Madhavan.

Reference books

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data by John Wiley & Sons
Python for Data Analysis by W McKinney
Think Stats: Probability and Statistics for Programmers by Allen B. Downey MOOC / NPTEL/YouTube Links: -
NPTEL Course: Data Science for Engineers https://onlinecourses.nptel.ac.in/noc25_cs20/preview
NPTEL Course: Python for Data Science https://onlinecourses.nptel.ac.in/noc25_cs60/preview

NPTEL and SWAYAM links

Listed in the official syllabus:

FAQ

How many units are in Data Science?

Data Science (MDM-271-INC) has 4 units: Unit I Data Science (5 h); Unit II Data Science Packages (8 h); Unit III Exploratory Data Analysis (6 h); Unit IV Data Cleaning and Data Visualization (7 h).

What is the marks scheme for Data Science?

The official Instrumentation and Control Engineering 2024 pattern syllabus lists continuous comprehensive evaluation (CCE) for 30 marks and the end-semester exam for 70 marks, for 2 credits.

What should I know before Data Science?

Prerequisite listed in the syllabus: Data Structure, Data Science Software Tools..