DATA 7302OL - Real Data: Modern Methods for Finding Hidden Patterns
Career: | Postgraduate Coursework |
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Units: | 3 |
Term: | Online Teaching Period 6 |
Campus: | Online |
Contact: | Up to 4 hours per week |
Restriction: | Graduate Diploma in Data Science (Applied) OL OR Master of Data Science (Applied) OL Only |
Available for Study Abroad and Exchange: | No |
Available for Non-Award Study: | No |
Pre-Requisite: | Carousel 1 Courses: COMP SCI 7212OL, COMP SCI 7210OL, DATA 7201OL & DATA 7202OL or MATHS 7203OL |
Assessment: | Assignment and/or exam |
Syllabus: |
This course builds upon DATA 7201OL Data Taming, to introduce advanced modern techniques for extracting meaningful information from real-world, messy datasets. The course covers methods such as generalised linear models, classification, advanced regression techniques, and unsupervised statistical learning. A particular focus will be data wrangling techniques for non-standard, big, “messy data”: natural language processing, networks and longitudinal data. The course teaches advanced R programming techniques for data science. |
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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Online Teaching Period 6 | Fri 04/10/2024 | Fri 01/11/2024 | Mon 18/11/2024 | Mon 02/12/2024 |
Class Details
Enrolment Class: Lecture | |||||||
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Class Nbr | Section | Size | Available | Dates | Days | Time | Location |
66006 | 01OL | 300 | 291 | This class does not have any timetabled face-to-face sessions. Please check MyUni or contact your Course Coordinator for details. |