STATS 7022 - Data Science PG
North Terrace Campus - Semester 2 - 2020
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General Course Information
Course Details
Course Code STATS 7022 Course Data Science PG Coordinating Unit Mathematical Sciences Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Y Assumed Knowledge STATS 2107 or (MATHS 2201 and MATHS 2202) or (MATHS 2106 and 2107). Experience with the statistical package R such as would be obtained from STATS 1005 or STATS 2107. Assessment Ongoing assessment and examination. Course Staff
Course Coordinator: Dr Jono Tuke
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
Syllabus:
The topics covered will include:
Overview of modelling framework
Preprocessing
Model theory
Resampling
Penalised regression
Classification modelling
LDA / SVM
Non-parametric
Trees
Random forests
Feature selection
Unsupervised learning
Learning outcomes:
On successful completion of this course, students will:
1. Demonstrate an understanding of the foundational principles of machine learning
2. Recognise which method to use for a given data analysis problem.
3. Demonstrate an understanding the statistical underpinning of the chosen method.
4. Implement safely any chosen method and interpret the results.
5. Be confident to apply the methods to large datasets.
6. Apply the theory in the course to solve a range of problems at an appropriate level of difficulty.最新糖心Vlog Graduate Attributes
No information currently available.
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Learning & Teaching Activities
Learning & Teaching Modes
The structure consists of
- Weekly topic videos watched in own time.
- One interpretation workshop a week held in the lecture time.
- One implementation workshop a week held in practical time.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload hours Topic videos 12 24 Interpretation workshop 12 24 Implementation workshop 12 24 Assignments 3 33 Online test 3 33 Online quizzes 12 18 Total 156 Learning Activities Summary
No information currently available.
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Assessment
The 最新糖心Vlog'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 Percent of final mark Online quizzes 5 Written assignments (3) 15 Test (3) 30 Written exam 30 Practical exam 20 Assessment Detail
Assessment Distributed Due Weighting A1 Week 2 Friday Week 4 5% A2 Week 6 Friday Week 8 5% A3 Week 10 Friday Week 12 5% Test 1 Week 2 10% Test 2 Week 6 10% Test 3 Week 10 10% Online quizzes Weekly Weekly 5% Practical exam TBD (week 12 or exam period) 20% Final exam Examination period 30% 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 .
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Student Feedback
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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 最新糖心Vlog 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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Student Support
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Policies & Guidelines
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- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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