Required texts

Students are not required to buy a specific textbook for this unit. However, it is strongly recommended that students use the following resources online and in the Library.

Recommended:

• Klosterman, S., 2019. Data Science Projects with Python: A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-learn. Packt Publishing Limited.
• Miell, I. and Sayers, A., 2019. Docker in practice. Simon and Schuster.
• Ryan, L., 2018. Visual Data Storytelling with Tableau: Story Points, Telling Compelling Data Narratives. Addison-Wesley Professional.
• Fregly, C., Barth, A. (2021). Data Science on AWS: Implementing End-To-End, Continuous AI and Machine Learning Pipelines. United States: O'Reilly Media, Incorporated.

Supplementary:

• Godsey, B., 2017. Think Like a Data Scientist: Tackle the data science process step-by-step. Simon and Schuster.
• Zheng, A. and Casari, A., 2018. Feature engineering for machine learning: principles and techniques for data scientists. " O'Reilly Media, Inc.".
• Wilke, C.O., 2019. Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media.
• Loth, A., 2019. Visual Analytics with Tableau. John Wiley & Sons.

Submission of assessment items

Extensions & Late submissions

Assignments are meant to be individual work, although talking a problem over with another student or tutor is considered one reasonable way of learning. However, the actual submitted assignment must be the student's own work. Students are expected to familiarise themselves with the University's Student Charter /Policies/PolicyProcedure/Index/200. Experience has shown that students who do not do their own work are unlikely to pass the unit.

Assignments will be submitted electronically through the Unit Website interface on º¬Ðß²ÝÊÓƵ LearnOnline.

Assignment submissions will be assessed for addressing the specific requirements of each assignment, as stated in the assignment descriptions. Assignment submissions will receive a numerical mark, which together in their entirety with the other assessment items define a student's final grade as outlined in this section.

Responsibility for understanding

If there is any doubt with regard to the requirements of any particular assignments or assessment procedure, the onus for clarifying the issue rests with the student who should contact the unit convenor or tutor. Further, it is the responsibility of students to ensure that they are correctly enrolled in the unit and that the lecturer/tutor and Student Administration have their correct contact details.

Special assessment requirements

In DSTS, students are required to satisfactorily complete the first assignment (i.e., a minimum of 25% of marks) and perform satisfactorily in a final project (i.e., a minimum of 50% of marks).

To obtain a particular grade in this unit, there must be no outstanding submissions at the end of week 15. The unit convener reserves the right to question students orally about any of their submitted work.

All assessment items will receive a numerical mark. The final grade will be determined as a weighted average of the individual assessment items (as described in Section 5a).

To be awarded a particular grade in DSTS, students must meet the assignments' overall requirements and requirements set out in the table below. All grades are conditional upon the following minimum requirements:

• Minimum 25% of marks in the first assignment (Assignment I) and
• Minimum 50% in the final project.

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Please note that the unit convenor reserves the right to question students on any of their submitted work for moderation and academic integrity purposes, which may result in an adjustment to the marks awarded for a specific task.

Supplementary assessment

Students who miss the final project due to illness or other acceptable grounds (see link below) may be able to sit for a deferred one. A doctor's certificate stating why the student was not able to submit for the assessment or other required evidence should be given to Student Central (Bldg. 1) as soon as possible - generally within 3 days of the submission due. See Assessment Policy /Policies/PolicyProcedure/Index/331 and Assessment Procedures /Policies/PolicyProcedure/Index/369 for more details. Students will only be allowed to sit for a deferred examination if there are no outstanding submissions or resubmissions for the assignments required to pass the subject as specified above.

Students must apply academic integrity in their learning and research activities at º¬Ðß²ÝÊÓƵ. This includes submitting authentic and original work for assessments and properly acknowledging any sources used.

Academic integrity involves the ethical, honest and responsible use, creation and sharing of information. It is critical to the quality of higher education. Our academic integrity values are honesty, trust, fairness, respect, responsibility and courage.

º¬Ðß²ÝÊÓƵ students have to complete the annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).

º¬Ðß²ÝÊÓƵ uses various strategies and systems, including detection software, to identify potential breaches of academic integrity. Suspected breaches may be investigated, and action can be taken when misconduct is found to have occurred.

Information is provided in the Academic Integrity Policy, Academic Integrity Procedure, and º¬Ðß²ÝÊÓƵ (Student Conduct) Rules 2023. For further advice, visit Study Skills.

Learner engagement

Participation requirements

Your participation in both class (lecture, tutorial/computer laboratory classes) and online activities will enhance your understanding of the unit content and therefore the quality of your assessment responses. Lack of participation may result in your inability to pass assessment items satisfactorily. Experience has shown that students who do not attend the classes and/or do not engage with the online content will have difficulty in passing the subject.

Required IT skills

Familiarity with using Windows or Mac computers and familiraity with writing and running python code.

In-unit costs

It is recommended to bring a USB stick/drive to the computer laboratory classes for additional backup.

Work placement, internships or practicums

Not applicable

Additional information

In all cases of absence, sickness, or personal problems, it is the student's responsibility to inform the unit convenor. The minimum participation requirement must be met to pass the unit (regardless of supporting documentation).

It is important that students refer to unit website (through º¬Ðß²ÝÊÓƵLearn – º¬Ðß²ÝÊÓƵ's online learning environment) on a regular basis for any variations in the schedule and deadlines for the assessment tasks, which will be announced on the Unit Website. It is also the student's responsibility to ensure that they regularly check their º¬Ðß²ÝÊÓƵ email account, as electronic messages (whether via the unit's º¬Ðß²ÝÊÓƵLearn site or directly) will be sent to this account.

The online discussion forum on the unit's º¬Ðß²ÝÊÓƵLearn site is as very useful place for posting questions and students are strongly encouraged to make use of it.

• Semester 2, 2024, On-campus, º¬Ðß²ÝÊÓƵ - Canberra, Bruce (218265)
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