Unit Outline
XPD125
Introduction to Data Science
IPC Semester 1, 2024
Elisabeth Widjojo
DVC - Academic
Academic Division (Division)
CRICOS Provider Code: 00586B

Unit Coordinator
Elisabeth Widjojo
Email: Elisabeth.Widjojo@utas.edu.au
What is the Unit About?
Unit Description
 

This unit will explain the relationship between data, information and knowledge and introduce a number of different methods/tools for managing, storing, securing, modelling, visualizing and analyzing. This unit will provide and understanding of how data can be manipulated to meet the needs of users. Changing data into information can be accomplished with a range of tools, including XML, SQL, spreadsheeting and data visualization. This unit introduces the techniques to enable the students to use these tools for managing data, creating information and allowing knowledge development. Overarching the whole unit is the importance of data security and how it can be achieved. This unit concludes by introducing the concepts behind managing big data in response to global trends of capturing all available data due to inexpensive storage.
Intended Learning Outcomes
As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.
On completion of this unit, you will be able to:
1.
Summarize and explore large data sets using appropriate numeric and graphical tools in order to communicate statistical concepts to both scientific and lay audiences.
2.
Recognize the key issues involved in designing a survey or experiment, and assess strengths and weaknesses in statistical arguments.
3.
Identify and apply appropriate statistical techniques to make inferences based on data.
4.
Perform common statistical analyses in a statistical computing package.
Requisites
REQUISITE TYPE
REQUISITES
Anti-requisite (mutual excl)
KIT102
Alterations as a result of student feedback
 
 
 

Teaching arrangements
ATTENDANCE MODE
TEACHING TYPE
LEARNING ACTIVITY
CONTACT HOURS
FREQUENCY
Attendance / engagement expectations
If your unit is offered On campus, it is expected that you will attend all on-campus and onsite learning activities. This is to support your own learning and the development of a learning community within the unit. If you are unable to attend regularly, please discuss the situation with your course coordinator and/or our UConnect support team.

If your unit is offered Online, it is expected you will engage in all those activities as indicated in the Unit Outline, including any self-directed learning.

If you miss a learning activity for a legitimate reason (e.g., illness, carer responsibilities) teaching staff will attempt to provide alternative activities (e.g., make up readings) where it is possible.
 
 
 
 

How will I be Assessed?
 
For more detailed assessment information please see MyLO.
Assessment schedule
ASSESSMENT TASK #
ASSESSMENT TASK NAME
DATE DUE
WEIGHT
LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:
Data Modelling Assignment
See the MyLO site for the due date
23 %
 
Assessment Task 2:
Weekly Tutorial Test
See the MyLO site for the due date
27 %
LO1, LO2, LO3, LO4
Assessment Task 3:
Examination
See the MyLO site for the due date
50 %
 
 
Assessment details
    
Assessment Task 1: Data Modelling Assignment
Task Description:
Data modelling assignment

Task Length:
 
Due Date:
See the MyLO site for the due date
Weight:
23 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
 
Assessment Task 2: Weekly Tutorial Test
Task Description:
Weekly tutorial test

Task Length:
 
Due Date:
See the MyLO site for the due date
Weight:
27 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Completion of task
LO1, LO2, LO3, LO4
 

 
Assessment Task 3: Examination
Task Description:
Final exam

Task Length:
 
Due Date:
See the MyLO site for the due date
Weight:
50 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
 
 
 

How your final result is determined
To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.
 
Submission of assignments
Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.
 
Requests for extensions
If you are unable to submit an assessment task by the due date, you should apply for an extension.
 
A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.
 
The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.
Late penalties
Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.
 
Review of results and appeals
You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.