| Code: | DTSC71-303 |
|---|---|
| Study areas: |
|
Description
Data analysis is the skill of the future. This subject identifies and critically analyses the concepts, theories and frameworks of big data research in a series of case studies. Through analysis and critique, students will develop an expert understanding of the research process and how the research presented in each case study has been relevant to both industry and the academic community. Students will synthesise the relevant literature, identify the big data techniques and interpret the results and evaluate their implications.
Subject details
Learning outcomes
- Apply knowledge from previous subjects in the discipline to a real big data project.
- Critically analyse and synthesise the relevant literature on an approved big data research topic.
- Evaluate the design of data collection and analyses from a given research question.
- Articulate the rationale, theory, methods, findings and implications of a research project in a professional written report.
- Deliver a clear, concise well-organised research presentation appropriate to specialist and non-specialist audiences using suitable visual aids.
Enrolment requirements
| Requisites: |
Pre-requisites:Co-requisites:There are no co-requisites |
|---|---|
| Assumed knowledge: |
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.
|
| Restrictions: |
This subject is not available to
This subject is not available as a general elective. To be eligible for enrolment, the subject must be specified in the students’ program structure. Anti-requisites: |