DATA 7302OL - Real Data: Modern Methods for Finding Hidden Patterns
Online - Online Teaching 6 - 2022
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General Course Information
Course Details
Course Code DATA 7302OL Course Real Data: Modern Methods for Finding Hidden Patterns Coordinating Unit Mathematical Sciences Term Online Teaching 6 Level Postgraduate Coursework Location/s Online Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange N Prerequisites Carousel 1 Courses: COMP SCI 7212OL, COMP SCI 7210OL, DATA 7201OL & DATA 7202OL Restrictions Graduate Diploma in Data Science (Applied) OL OR Master of Data Science (Applied) OL Only Assessment Assignment and/or exam Course Staff
Course Coordinator: Professor Lewis Mitchell
Course Timetable
The full timetable of all activities for this course can be accessed from Course Planner.
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Learning Outcomes
Course Learning Outcomes
- create a predictive model for classification (predict classes) from real data using the TidyModels package in R
- create a predictive model for regression (predict numbers) from real data using the TidyModels package in R
- identify when predictive modelling is not giving accurate predictions due to overfitting
- apply cross-validation to avoid overfitting
- contrast the performance of prediction models to assess their viability
- analyse unsupervised data to find the patterns and represent the patterns visually
- communicate results of the interpretation and analysis of predictive modelling.
University Graduate Attributes
No information currently available.
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Learning & Teaching Activities
Learning & Teaching Modes
No information currently available.
Workload
No information currently available.
Learning Activities Summary
No information currently available.
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Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
Assessment consists of
Type of assessment Week(s) due Weighting Quizzes 1,2,3,4,5,6 20% total Case Study 1 4 30% Case Study 2 end of course 50%
Assessment Detail
No information currently available.
Submission
No information currently available.
Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Phone: 1800 512 155 (24/7)
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Email: info@assureprograms.com.au
Go to the Study Smart Hub to learn more, or speak to your Student Success Advisor (SSA) on 1300 296 648 (Monday to Thursday, 8.30am–5pm ACST/ACDT, Friday, 8.30am–4.30pm ACST/ACDT)
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
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- Modified Arrangements for Coursework Assessment Policy
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- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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