Subject Details
Dept     : AIDS
Sem      : 5
Regul    : 2019
Faculty : PRIYADHARSHINI.S
phone  : 9943082082
E-mail  : priyadharshini.s.ad@snsce.ac.in
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Syllabus

UNIT
1
INTRODUCTION TO DATA SCIENCE AND BIG DATA

Terminologies Used in Big Data Environments – Types of Digital Data – Classification of Digital Data – Introduction to Big Data – Characteristics of Data – Evolution of Big Data – Big Data Analytics – Classification of Analytics – Top Challenges Facing Big Data – Importance of Big Data Analytics – Data Analytics Tools

UNIT
2
PYTHON PACKAGES FOR DATA ANALYTICS

Numpy: Numpy Data types, Scipy, Jupyter, Statsmodels and Pandas Package – Scikit learn, R programming .

UNIT
3
BIG DATA ANALYTICS FRAMEWORKS

Introducing Hadoop – Hadoop Overview – RDBMS versus Hadoop – HDFS (Hadoop Distributed File System): Components and Block Replication – Processing Data with Hadoop – Introduction to MapReduce – Features of MapReduce, YARN, HBASE

UNIT
4
DATA PREPARATON AND VISUALIZATION

Data Munging: Introduction to Data Munging, Data Pipeline and Machine Learning in Python – Data Visualization Using Matplotlib – Interactive Visualization with Advanced Data Learning Representation in Python

UNIT
5
BIG DATA DATABASES

Introduction to NoSQL: Types of NoSQL Databases-Key-value store, Document store, Column family, Graph store, CAP theorem – CAP Theorem NoSQL databases, MongoDB: RDBMS VsMongoDB – Mongo DB Database Model – Data Types, Sharding –Types of sharding, Introduction to Hive – Hive Architecture – Hive Query Language (HQL)

Reference Book:

Alberto Boschetti, Luca Massaron, “Python Data Science Essentials”, Packt Publications, 2nd Edition, 2016 VDT Editorial Services, Big Data, Black Book, Dream Tech Press, 2015 Yuxi (Hayden) Liu, “Python Machine Learning”, Packt Publication, 2017.

Text Book:

Frank Pane, “Hands On Data Science and Python Machine Learning”, Packt Publishers, 2017 Seema Acharya, SubhashiniChellapan, “Big Data and Analytics”, Wiley, 2015.