As part of the course architecture redevelopment, the 3rd year data science project is being introduced as a ?capstone? project running over 12 credit points. This is part 2 of that project. It corresponds to the CS version FIT3162.

Introduced for course architecture programs. Effective semester 1, 2016

Reason for changes made on 15/06/2016: Collaborative teamwork is made an explicit ULO.

July 2018: Updated workload requirements on behalf of CE to match CS project and DS project part 1.

05/10/2020 Admin: Update to include new assessment and teaching approach fields as per Handbook requirements

9/07/2021 CE: More even distribute of assessments across the semester, and improved tracking of student progress with weekly progress reports.

Core in the BCS degree with Data Science specialisation, capstone research project (part 2).

On completion of this unit, students should be able to:

1. evaluate and select research methods and techniques of data preparation and analysis appropriate to a particular project;
2. search, access, and analyse research literature as part of the process of developing solutions to problems;
3. work effectively in collaborative teams;
4. develop and test a substantial piece of software or perform a substantial analysis of data using software;
5. explain and reflect upon the purpose, operation, success and value of the developed project in writing and orally;
6. write a report explaining methodology, outlining their contributions and the contributions of others, and documenting the developed project from appropriate perspectives, for instance that of a user, researcher or developer.

029900

This unit provides practical experience in researching, designing, developing and testing a non-trivial data science project. Projects involve whole or part of the data science process (visualisation, analysis, algorithms, etc.) but can also be software-based, or they may involve investigation of theory. Projects if software-based should cover analysis through design to implementation and testing. Comprehensive written documentation on the project is required. Students are assigned in groups to a project supervisor. There are no lectures in this unit, although students will be expected to attend regular meetings with their project supervisor. The unit is the second part of a 12-credit point project sequence; the first part and entry point for the project is FIT3163.

Learning resources, including project specifications and project reading material, will be provided by the lecturers on Moodle. In addition, any research papers pertaining to the project will be available from the Monash Library.

Technological requirements

(For Clayton Campus ONLY) Please note: This is a bring your own device unit. You will be expected to bring a web-connected device (i.e., laptop or tablet) to class to access specialist software. The applications for your class can be accessed at the website move.monash.edu

On-campus

Problem-based learning Students (in teams) who have completed the initial planning and research in FIT3163 are now required to fully implement their data science project. Students are encouraged to take responsibility for organising and directing their learning with support from their supervisors.

Seminars

Students will also be introduced to various aspects of data science research and project development in seminars run by guest lecturers.

In-semester assessment: 100%

1. Journal Entries: - 5% - ULO: 1, 3, 4, 5, 6
2. Interim Presentation: - 5% - ULO: 3, 4, 5
3. Final Presentation: - 10% - ULO: 3, 4, 5
4. Software Deliverable: - 25% - ULO: 1, 2, 3, 4, 5, 6
5. Final Report: - 35% - ULO: 1, 2, 3, 4, 5, 6
6. Team Management: - 5% - ULO: 3
7. Weekly Progress Reports: - 5% - ULO: 1, 2, 3, 4, 5, 6
8. Project Management Reports: - 10% - ULO: 1, 2, 3, 5, 6

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

• 2-hour project meeting and peer-learning session per week in a lab environment.
• 2-hour guest lectures and peer presentations in seminars.

(b.) Additional requirements (all students):

• A minimum of 8 hours of personal study in order to complete the research and implementation of the project.

FIT3163