FIT1043 - Introduction to data science - 2019

This unit looks at processes and case studies to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Working with data as part of a business model and the lifecycle in an organisation is considered, as well as business processes and case studies. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage and basic kinds of data preparation, data cleaning and data stream processing. Curation and management are reviewed: archival and architectural practice, policy, legal and ethical issues. Styles of data analysis and outcomes of successful data exploration and analysis are reviewed. Standards, tools and resources are also reviewed.

At the completion of this unit, students should be able to:

1. explain the role of data in different styles of business;
2. demonstrate the size and scope of data storage and data processing, and classify the basic technologies in use;
3. identify tasks for data curation and management in an organisation;
4. classify participants in a data science project: such as statistician, archivist, analyst, and systems architect;
5. classify the kinds of data analysis and statistical methods available for a data science project;
6. locate suitable resources, software and tools for a data science project.

NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for students:
   • Two hours lectures
   • Two hours laboratories
2. Additional requirements:
   • A minimum of 8 hours of personal study per week in order to satisfy the reading, tute, prac and assignment expectations.

See also Unit timetable information

Data science