Program Outcome For BACHELOR OF SCIENCE IN DATA SCIENCE
PO1: Build a strong foundation of statistics for data science.
PO2: Use all the features and new updates of Python and R for data science.
PO3: Perform scientific and technical computing using the Python Sci Py package and
its sub- packages Integrate, Optimize, Statistics, IO, and Weave.
PO4: Gain expertise in mathematical computing using the Num Py and Sci kit-Learn
package.
PO5: Gain an in-depth understanding of data structure and data manipulation.
PO6: Understand and use linear and non-linear regression models and classification
techniques for data analysis
PO7: Obtain a comprehensive knowledge of supervised and unsupervised learning
models such as linear regression, logistic regression, clustering, dimensionality
reduction, K-NN and pipeline.
PO8: Master the concepts recommendation engine, time series modelling, gain
practical mastery over principles, algorithms, and applications of Machine Learning.
PO9: Learn to analyze data using Tableau and Power BI and become proficient in
building interactive dashboards.
PO10: Understand deep reinforcement learning techniques applied in Natural
Language Processing
PO11: Understand the different components of the Hadoop ecosystem and learn to
work with H Base, its architecture and data storage, learning the difference between H
Base and RDBMS, and use Hive and Impala for partitioning
PO12: Understand Map Reduce and its characteristics and learn how to in gest data
using Sqoop and Flume