Data Capture and Preparations (12122.1)
| Available teaching periods | Delivery mode | Location |
|---|---|---|
| View teaching periods | On-campus |
Bruce, Canberra |
| EFTSL | Credit points | Faculty |
| 0.125 | 3 | Faculty Of Science And Technology |
| Discipline | Study level | HECS Bands |
| School Of Information Technology & Systems | Level 3 - Undergraduate Advanced Unit | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
Learning outcomes
Upon successful completion of this unit, students will be able to:1. Work with sensors for capturing data;
2. Choose and apply appropriate techniques for capturing data from existing sources;
3. Import data into R;
4. Convert data from one format to another one in R;
5. Employ suitable techniques for tidying data; and
6. Develop a sound understanding of text mining methods in R.
Graduate attributes
1. UC graduates are professional - communicate effectively1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Prerequisites
11372 Introduction to Data ScienceCorequisites
None.Incompatible units
11520 Data Capture and Preparations GEquivalent units
None.Assumed knowledge
Working knowledge of discrete mathematics, algebra and numerical analysis.| Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
|---|---|---|---|---|---|
| 2026 | Bruce, Canberra | Semester 1 | 16 February 2026 | On-campus | Dr Raul Fernandez Rojas |
| 2027 | Bruce, Canberra | Semester 1 | 15 February 2027 | On-campus | Dr Raul Fernandez Rojas |
Required texts
There is no required textbook for this unit. However, the following are recommended readings that a re a companion for the concepts taught in this unit.
Recommended:
"R in Action – Data analysis and Graphics with R" by Robert Kabacoff
"R for Data Science" by Garrett Grolemund and Hadley Wickham
"Practical Data Science with R" Second Edition by Nina Zumel and John Mount
A limited number of copies of these books are also available from the UC Library.
Submission of assessment items
Extensions & Late submissions
GenAI - Guided: Students will be guided in how GenAI must/may be used in completing the assessment as detailed in the unit outline and assessment instructions. More detailed information can be found at GenAI and Assessment at UC. Guided: Means the convener will permit students to ethically use GenAI in some assessments but not all of them, with guidance and as outlined by each assessment description.
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 https://www.canberra.edu.au/Policies/PolicyProcedure/Index/200. Experience has shown that students who do not do their own work are unlikely to pass the exam (and therefore the unit).
Assignments will be submitted electronically through the Unit Website interface on UC LearnOnline. For the two assignments, students need to submit their files as a ZIP file via the unit's UC LearnOnline site.
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 (tests, exam) define a student's final grade as outlined in this section.
Extensions: Extensions must be applied for before the due date.
Students can apply for an extension to the due date for submission of an assessment item on the grounds of illness or other unavoidable and verifiable personal circumstances as described under "Acceptable Grounds for Approval" at http://www.canberra.edu.au/student-services/examinations/alternative-exams. Documentary evidence will be expected in order that an extension be granted. Applications need to use the above mentioned Assignment Extension form.
It should be noted that such documentation will be considered but will not guarantee that the application will be successful. The Unit Convenor will decide whether to grant an extension and the length of the extension.
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 tutor and Student Administration have their correct contact details.
Special assessment requirements
To obtain a particular grade in this unit, it is necessary that there are no outstanding submissions at the end of week 14. The unit convener reserves the right to question students orally on 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.
To be awarded a particular grade in DCP, students must meet the following requirements as set out below. All grades are conditional upon the following minimum requirements:
- Minimum 50% of available marks in the total mark (Assingments + Quizzes + Early Assessment)
| Grade |
Assignments + Quizzes + Early Assessment |
| Pass |
Minimum 50% of combined weighted marks of all assessment items |
| Credit |
Minimum 65% of combined weighted marks of all assessment items |
| Distinction |
Minimum 75% of combined weighted marks of all assessment items |
| High Distinction |
Minimum 85% of combined weighted marks of all assessment items |
Supplementary assessment
Students who miss any assignment due to illness or other acceptable grounds (see link below) should submit an Assignment Extension Form accompanied with a doctor's certificate stating why the student was not able to complete the assessment on time or other required evidence should be given to Student Central (Bldg. 1) as soon as possible - generally within 3 days of the deadline. See Assessment Policy https://www.canberra.edu.au/Policies/PolicyProcedure/Index/331 and Assessment Procedures https://www.canberra.edu.au/Policies/PolicyProcedure/Index/369 for more details.
Students must apply academic integrity in their learning and research activities at UC. 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.
UC students have to complete the Academic Integrity Module annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).
UC 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 University of Canberra (Student Conduct) Rules 2023. For further advice, visit Study Skills.
Learner engagement
Expected Average Student Workload: * denotes an assessable item
| Lectures | 12x 2h | = 24h |
| Tutorials / Computer laboratory classes | 12x 2h | = 24h |
| Preparation (lectures, computer labs, reading, unsupervised activities) | 12x 3h | = 36h |
| * Assignment 1 – Data capture using sensors | . | = 23h |
| * Assignment 2 – Web scraping | . | = 23h |
| * Early Assessment | . | = 5h |
| * Online Quizzes (incl. preparation) | . | = 15h |
Total 150 hours
Participation requirements
Research has established that there is a strong correlation between engagement and success in higher education. With this in mind, we encourage you to actively participate in all activities to enhance your learning opportunities. Unless specifically stated in the unit outline, there is no mandatory attendance requirement. However, you may elect to attend these, as they allow you to ask 'real time' questions to develop your understanding for the relevant assessment tasks.
Required IT skills
Fundamental R programming concepts, usage of Windows computers.
In-unit costs
2x USB thumb drives and consumables
Work placement, internships or practicums
Not applicable to this unit
Additional information
In all cases of absence, sickness or personal problems, it is the student's responsibility to ensure that the unit convenor is informed.
It is important that students refer to unit website (through UCLearn – UC'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 UC email account, as electronic messages (whether via the unit's UCLearn site or directly) will be sent to this account.
The online discussion forum on the unit's UCLearn site is as very useful place for posting questions and students are strongly encouraged to make use of it.
