This unit is a duplicate unit of FIT5196. 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. Parse data in the required format;
2. Assess the quality of data for problem identification;
3. Resolve data quality issues ready for the data analysis process;
4. Integrate data sources for data enrichment;
5. Document the wrangling process for professional reporting;
6. Write program scripts for data wrangling processes.

020399

This unit introduces tools and techniques for data wrangling. It will cover the problems that prevent raw data from being effectively used in analysis and the data cleansing and pre-processing tasks that prepare it for analytics. These include, for example, the handling of bad and missing data, data integration and initial feature selection. It will also introduce text mining and web analytics. Python and the Pandas environment will be used for implementation.

On-campus

In-semester assessment: 100%

Minimum total expected workload equals 144 hours per semester comprising:

1. Contact hours for on-campus students:
   • Two hours/week lectures
   • Two hours/week tutorials
2. Additional requirements:
   • A minimum of 8 hours per week of personal study (22 hours per week for Monash online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

FIT

ITI9136