STATS 4022 - Data Science - Honours
Career: | Undergraduate |
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Units: | 3 |
Term: | Semester 2 |
Campus: | North Terrace |
Contact: | Up to 3 hours per week |
Restriction: | Honours students only |
Available for Study Abroad and Exchange: | Yes |
Available for Non-Award Study: | No |
Pre-Requisite: | STATS 2107 or (MATHS 2201 and MATHS 2202) or (MATHS 2106 and MATHS 2107) |
Assumed Knowledge: | Experience with the statistical package R such as would be obtained from STATS 1005 or STATS 2107. |
Incompatible: | STATS 3022 |
Assessment: | Ongoing assessment and examination. |
Syllabus: |
This course will introduce the fundamental concepts of modern data science. It will provide students with tools to deal with real, messy data, an understanding of the appropriate methods to use, and the ability to use these tools safely. Topics will include data structures; regression models including lasso regression, ridge regression and non-linearity with splines; classification models including logistic regression, linear discriminant analysis, support vector machines and random forests; and unsupervised learning methods such as principal component analysis, k-means and hierarchical clustering. The practical skills will be focused on data science in R. |
Course Fees
Study Abroad student tuition fees are available here
Only some Postgraduate Coursework programs are available as Commonwealth Supported. Please check your program for specific fee information.
The fees displayed below for international students are for students commencing a program in 2024 only. International students who commenced a program in 2023 or prior can find their fee here.
EFTSL | |||
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0.125 |
Course Outline
A Course Outline which includes Learning Outcomes, Learning Resources, Learning & Teaching for this course may be accessed here
Critical Dates
Term | Last Day to Add Online | Census Date | Last Day to WNF | Last Day to WF |
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Semester 2 | Mon 05/08/2024 | Wed 14/08/2024 | Fri 13/09/2024 | Fri 25/10/2024 |
Class Details
Enrolment Class: Workshop | |||||||
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Class Nbr | Section | Size | Available | Dates | Days | Time | Location |
20417 | WR01 | 5 | 5 | 22 Jul - 9 Sep | Monday | 3pm - 4pm | Ingkarni Wardli, 234, CAT Suite |
30 Sep - 21 Oct | Monday | 3pm - 4pm | Ingkarni Wardli, 234, CAT Suite | ||||
Related Class: Practical | |||||||
Class Nbr | Section | Size | Available | Dates | Days | Time | Location |
24755 | PR01 | 5 | 5 | 26 Jul - 13 Sep | Friday | 9am - 10am | Engineering & Mathematics, EMG13, Computer Suite |
4 Oct - 25 Oct | Friday | 9am - 10am | Engineering & Mathematics, EMG13, Computer Suite |