COMP 3035 Discovery Project

Credit Points 10

Legacy Code 301490

Coordinator Rosalind Wang Opens in new window

Description In this subject students will gain experience in applying data science skills and using knowledge gained during their bachelor's course of their primary discipline. Students will carry out a real life project transforming data to knowledge under the supervision of an academic mentor. Students will develop a knowledge discovery project proposal and carry out a literature review highlighting the current status of the problem. Assisted by a mentor they will apply the data science skills learned through-out the degree and produce a final discovery project report and/or interactive project tool and give an oral presentation.

School Computer, Data & Math Sciences

Discipline Computer Science, Not Elsewhere Classified.

Student Contribution Band HECS Band 2 10cp

Check your HECS Band contribution amount via the Fees page.

Level Undergraduate Level 3 subject

Restrictions

Students in following programs must have completed 160 credit points before enrolling into the subject: 3754 Bachelor of Science 3756 Bachelor of Science (Pathway to Teaching Primary/Secondary) 3769 Bachelor of Data Science.

Students in following programs must have completed 200 credit points before enrolling into the subject: 2743 Bachelor of Science/Bachelor of Laws 3757 Bachelor of Advanced Science 3763 Bachelor of Science/Bachelor of Arts 3764 Bachelor of Science/Bachelor of International Studies 3770 Bachelor of Applied Data Science 3778 Bachelor of Mathematics 4748 Bachelor of Science/Bachelor of Business 6043 Diploma in Science/Bachelor of Science

Learning Outcomes

1. Design a data driven knowledge discovery project plan and develop an investigative project proposal
2. Collect, integrate, clean and prepare the data source relevant to the problem being studied
3. Undertake self-directed study and literature search relevant to the problem being investigated
4. Undertake a computational and/or analytical approach in problem solving and predictive modelling
5. Undertake a multidisciplinary project
6. Write and produce a comprehensive research report in a logical, concise and professional manner
7. Present a project and its results to an audience in an oral presentation

Subject Content

This subject will cover and include, research methodology, reference management software, literature search, theses writing skills, theses writing software and power point and presentation skills. The projects offered will vary according to the expertise and the research interests of students and the academic supervisors. Students will choose individual project topics and the relevant data from their concurrent degree in consultation with the subject coordinator and the supervising staff member (mentor). Students will gain a hands-on experience in solving a real life problem by applying both statistical and computational skills gained by data science component to data in data storage, processing and analysis. Hence these projects will have a common flavour of being data driven and multidisciplinary and will highlight the capabilities of data science approach.

Assessment

The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.

Item Length Percent Threshold Individual/Group Task
Written Project Outline 1,000 words 10 N Group
Presentation of Project Outline 10 minutes 10 N Group
Report 4,000 words 45 N Group
Presentation 30 minutes 25 N Group
Supervisor's assessment of the student's self-directed project work N/A 10 N Group

Teaching Periods

Autumn

Parramatta - Victoria Rd

Day

Subject Contact Rosalind Wang Opens in new window

View timetable Opens in new window

Spring

Parramatta - Victoria Rd

Day

Subject Contact Rosalind Wang Opens in new window

View timetable Opens in new window