This unit is a duplicate unit of FIT5202. The ITIxxxx units have been created for the Monash Indonesia offering of the Master of Data Science due to the different teaching mode.

On successful completion of this unit, you should be able to:

1. identify and explain big data concepts and technologies;
2. write and interpret parallel database processing algorithms and methods;
3. apply common data analytics and machine learning algorithms in a big data environment;
4. use and evaluate streaming methods in big data processing;
5. use big data streaming technologies.

020399

This unit focuses on big data processing, including volume, complexity, and velocity using the latest big data technologies. In big data volume, it covers large volume data processing using parallel technologies. In large dimensionality (or complexity), it covers various data analytics methods for parallel processing. For the velocity, it covers data streaming processing.

On-campus

Examination (2 hours and 10 minutes): 60%; In-semester assessment: 40%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures.
   • Two hours/week laboratories.
2. Additional requirements:
   • A minimum of 8 hours per week of personal study for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

FIT

ITI9136 and ITI9132