Page 88 - PG-Handbook23-24-finale

4. Implement parallel and distributed systems.

Synopsis of Course Content
This course focuses on the design and implementation of parallel and distributed processing systems.
This course covers the fundamental concepts of distributed computing and introduces contemporary
issues in big-data processing. This course emphasises on both the underlying principles and hands-
on experience of data analytic tools.

Evaluation and Weightage
Continuous Assessment : 50%
Final Examination : 50%

WQD7009 Big Data Applications and Analytics

Learning Outcomes
At the end of this course, students are able to:
1. Explain the concepts of Big Data Applications and Analytics
2. Use suitable methods and techniques to analyse big data
3. Evaluate big data problems and suggest solutions to a real world problem

Synopsis of Course Content
The course will cover Big data applications and analytics, Data Collection, Sampling and Pre-
processing, Predictive Analysis, Descriptive analysis, Survival analysis, Social networks analysis, and
Case study of Big data Applications.

Evaluation and Weightage
Continuous Assessment : 70%
Final Examination : 30%

WQD7010 Network and Security

Learning Outcomes
At the end of the course, students are able to:

1. Investigate the concept of network and the criteria of having a secure network and the latest
network security issues.
2. Experiment a secured network.
3. Evaluate a secured network and its mechanism.

Synopsis of Course Content
The course consists of the advanced network, the concepts of securing a network, applying security
perimeters, implement secure access to network devices and infrastructures, implement firewall and
IPS.

Evaluation and Weightage
Continuous Assessment : 50%
Final Examination : 50%