Programming for Data Science G (11521.1)

Please note these are the 2023 details for this unit
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Programming for Data Science G
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
Academic Program Area - Technology Graduate Level Band 2 2021 (Commenced After 1 Jan 2021)
Band 3 2021 (Commenced Before 1 Jan 2021)
Beyond the foundational knowledge of using R for data science, data scientists need to be proficient in valuable programming tools and languages that form the basis of advanced analysis and modelling techniques. Using real-world data sets and a problem-solving framework, students in this unit will learn industry-standard programming skills and best practises for data organisation, data manipulation, data interrogation and data modelling relevant to data science. Students will develop a sound understanding of technical programming in one or more languages and related computational modelling and analysis tools. This includes skills in software engineering, such as writing correct code, working with version control tools, testing and debugging. A particular emphasis will be on tackling real-world data science problems as found in industry.

Learning outcomes

After successful completion of this unit, students will be able to:
1. Learn fundamentals of programming in Python and/or other relevant languages;
2. Develop a sound understanding of the most common libraries and tools;
3. Learn how to connect to large databases;
4. Demonstrate strong skills in good software engineering practices, such as writing correct code, testing and debugging, based on industry standards and best practices;
5. Learn how to use version control tools;
6. Critically reflect on available computational tools for solving data science problems; and
7. Successfully demonstrate practical skills in developing solutions to data science problems.


Graduate attributes

1. 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 - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
3. UC graduates are lifelong learners - evaluate and adopt new technology
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - take pride in their professional and personal integrity
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas


Prerequisites

11516 Introduction to Data Science G

Corequisites

None.

Incompatible units

None.

Equivalent units

None.

Assumed knowledge

Working knowledge of discrete mathematics, algebra and numerical analysis.
Year Location Teaching period Teaching start date Delivery mode Unit convener
2024 Bruce, Canberra Semester 1 05 February 2024 On-Campus Dr Ghazal Bargshady
2024 Bruce, Canberra Semester 2 29 July 2024 On-Campus Dr Ghazal Bargshady
Not available

Required texts

Students are not required to buy a textbook for this unit.

Lecture materials, tutorial questions and answers, assignment specifications, and other related information are required. Details will be provided on UCLearn (Canvas) website for the unit.

The following website and textbook are recommended:

Submission of assessment items

Extensions & Late submissions

Where possible, all assessment items will be submitted online via the teaching site in UCLearn. The first page of each assessment item should include the following information:

  • Student ID number:
  • Assessment Name:
  • Word Count (if applicable):

Special assessment requirements

For Final Assessment in the unit, the result will be one of the following grades: HD, DI, CR, P, or Fail (NX, NC or NN). Late submission in Final Assessment is not allowed.

The final mark is calculated as follows:

Final mark (out of 100) = Quiz 1 mark (out of 10) + Assignment 1 mark (out of 20) + Quiz 2 mark (out of 10) + Assignment 2 mark (out of 20) + Assignment 3 mark (out of 40)

All grades are conditional upon the following requirements:

  • Achieve an aggregate of at least 40 (50%) over all Assignments (i.e., Ass1 + Ass2 + Ass3 score >= 40). 

The final grade for the subject is then determined according to the following table:

85 <= Final mark <= 100

Final grade = HD

75 <= Final mark < 85

Final grade = DI

65 <= Final mark < 75

Final grade = CR

50 <= Final mark < 65

Final grade = P

0 <= Final mark < 50

Final grade = FAIL (NX, NC or NN)

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.

Academic integrity

Students have a responsibility to uphold University standards on ethical scholarship. Good scholarship involves building on the work of others and use of others' work must be acknowledged with proper attribution made. Cheating, plagiarism, and falsification of data are dishonest practices that contravene academic values. Refer to the University's Student Charter for more information.

To enhance understanding of academic integrity, all students are expected to complete the Academic Integrity Module (AIM) at least once during their course of study. You can access this module within UCLearn (Canvas) through the 'Academic Integrity and Avoiding Plagiarism' link in the Study Help site.

Use of Text-Matching Software

The University of Canberra uses text-matching software to help students and staff reduce plagiarism and improve understanding of academic integrity. The software matches submitted text in student assignments against material from various sources: the internet, published books and journals, and previously submitted student texts.

Learner engagement

Activities

 Estimated hours per week

 Weekly Lecture on Canvas: 2 hours per week, 12 weeks

24

 Weekly Tutorial: 1 hour per tutorial,  12 weeks

12

 Weekly study commitment and online taks, in addition to the 2 items above: 3 hours per week, 12 weeks

36

 Assignments : 68 hours 

78

 Total

150

Participation requirements

Your participation in both lecture and lab/tutorial 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 satisfactorily pass assessment items. To pass the unit, you must (1) achieve over a 50% aggregate over all assessments, and (2) achieve an aggregate of at least 40 (50%) over all Assignments (i.e., Ass1 + Ass2 + Ass3 score >= 40). Consistent attendance and engagement with the unit lectures, tutorials and study material can help you achieve (1) and (2). 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

Common IT skills, such as writing a report electronically, using web browsers are also required.

Work placement, internships or practicums

None

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. The minimum participation requirement must be met in order to pass the unit (regardless of supporting documentation).

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.