Courses & Units
Introduction to Data Science KIT102
Introduction
This unit will explain the relationship between data, information, and knowledge and introduce several different methods/tools for managing, storing, securing, modelling, visualising, and analysing data. This unit will provide an 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 Splunk, SQL, and Python. This unit introduces the techniques to enable the students to use these tools for managing data, visualising data, creating information, and allowing knowledge development. Overarching the whole unit is the importance of data security and how it can be achieved.
Completing this unit will provide you with the opportunity to prepare for the Splunk Core Certified User certification exam.
Students need to get permission from the unit coordinator to enrol in the online offering. This online offering is primarily for students enrolled in the Diploma of ICT Professional Practice (including the Undergraduate Certificate in ICT Professional Practice) or the Business Analytics major in the BBus who might need to complete the unit online. Online students will need to attend an online tutorial.
Summary
| Unit name | Introduction to Data Science |
|---|---|
| Unit code | KIT102 |
| Credit points | 12.5 |
| College/School | College of Sciences and Engineering School of Information and Communication Technology |
| Discipline | Information & Communication Technology |
| Coordinator | Doctor Son Tran |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
| Level | Introductory |
Availability
| Location | Study period | Attendance options | Available to | ||
|---|---|---|---|---|---|
| Hobart | Semester 2 | On-Campus | International | Domestic | |
| Launceston | Semester 2 | On-Campus | International | Domestic | |
| Online | Semester 2 | Off-Campus | International | Domestic | |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Note
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Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
Key Dates
| Study Period | Start date | Census date | WW date | End date |
|---|---|---|---|---|
| Semester 2 | 10/7/2023 | 8/8/2023 | 28/8/2023 | 15/10/2023 |
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2023 are indicative and subject to change. Finalised census dates for 2023 will be available from the 1st October 2022. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Securely store, convert and query data, information, and knowledge
- Extract and analyse knowledge and information from data
- Apply ICT knowledge, skills, and tools to design and develop efficient solutions to data-based problems
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| 029999 | $1,037.00 | $1,037.00 | not applicable | $2,522.00 |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Teaching
| Teaching Pattern | Lectures: 1hr/wk |
|---|---|
| Assessment | Weekly Tutorial Test (30%)|Data Exploration Assignment (20%)|Data Modelling Assignment (20%)|Data Mining Assignment (30%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
|---|
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.