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This capstone subject for the Data Science major combines statistical reasoning and practical computing skills to solve challenging problems with big data.
Students will learn about communication of quantitative information and insights; presentation skills; report writing; project management; problem formulation using case studies; data collection and measurement protocols; data from surveys and experiments; issues in capturing and dealing with “big data”; dimension reduction; data visualisation; fitting formulated models to data to infer insightful information about populations; ethics in quantitative research; working effectively in teams.
Intended learning outcomes
On completion of this subject students should be able to extract useful information from large data sets. In particular they should be able to:
- Display data in a manner that highlights its principal structures
- Formulate problems presented to them according to data science principles
- Organise and structure data for the purposes of analysis, particularly "big data"
- Fit and refine models
- Understand the dynamics of working in a team
- Communicate effectively with team members and non-technical subject matter experts
- Harness the collective skills in a team to achieve an efficient outcome
- Apply sound ethical principles to ethical issues that arise in data science
- Interpret the results of analysis and communicate insights effectively
In addition to learning specific statistical and computational skills, in this subject you will have the opportunity to develop generic skills that will assist you in your future career. You will develop communication, co-operation and problem solving skills (especially through the group assignment), such as how to come up with relevant strategies to solve unfamiliar problems. You will develop skills in working as a team, and you will develop analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms.
Last updated: 24 January 2023