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Unit of study_

OLET1603: Analysing and Plotting Data: Python

Intensive August, 2020 [Online] - Camperdown/Darlington, Sydney

This unit is a gentle on-line OLE introduction into coding using the popular script language Python for students who do not receive these skills in junior units of study. Through working through examples in on-line exercises and regular assessment and support hours, the students will develop hands-on skills. In particular the unit will teach analysis of text based data, numerical data and categorical data, constructing plots and developing summaries. Note that the unit only runs in the first 5 weeks of the main Semester 2 teaching period.

Unit details and rules

Unit code OLET1603
Academic unit Life and Environmental Sciences Academic Operations
Credit points 2
Prohibitions
? 
INFO1903 or COMP5310 or DATA1002 or OLET1601
Prerequisites
? 
None
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Willem Vervoort, willem.vervoort@sydney.edu.au
Type Description Weight Due Length
Tutorial quiz On-line completion: quizzes at the end of the module
On-line quiz at the end of each module
50% Multiple weeks not timed
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Final exam (Open book) Type C final exam Final exam
Short open answer coding questions
50% Week 08 1 hour
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Type C final exam = Type C final exam ?

Assessment summary

The quizzes are self guided on-line quizzes. Quiz 1 and 2 are “auto-marked”, while quiz 3 and 4 are marked manually by staff.

Quizzes are generally due one week after the module is discussed in the tutorial.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Multiple weeks 1 hour consultation to support the on-line learning Tutorial (1 hr) LO1 LO2 LO3 LO4 LO5
Weekly Self-guided work on the modules. Complete module 1 and quiz 1 by week 3, complete module 2 and quiz 2 by week 4, complete module 3 and quiz 3 by week 5 and complete module 4 and quiz 4 by week 6 Online class (4 hr) LO1 LO2 LO3 LO4 LO5

Attendance and class requirements

The tutorials are non-compulsory, but highly recommended.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 2 credit point unit, this equates to roughly 40-50 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. read in and write out data into Python in common formats (csv, txt) from a directory or from an internet source
  • LO2. inspect the data in tabular form in Python and do element, column and row manipulations using text and numerical data
  • LO3. produce statistical summaries of numerical data, text based data and subsets of data
  • LO4. demonstrate a basic understanding of packages and libraries and load and use some common libraries in Python
  • LO5. use basic graphics to display the data using x-y plots, bar plots and histograms, and manipulate axis, colours, lines, points and labels

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

Unit was updated based on comments from students in 2018 when the unit ran for the first time.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.