MATHS 1004 - Mathematics for Data Science I
North Terrace Campus - Semester 2 - 2024
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General Course Information
Course Details
Course Code MATHS 1004 Course Mathematics for Data Science I Coordinating Unit Mathematical Sciences Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Y Prerequisites At least a C- in SACE Stage 2 Mathematical Methods or IB Mathematics: at least 3 in Applications and Interpretations HL; or 4 in Analysis and Approaches SL Incompatible MATHS 1008, MATHS 1010, MATHS 1012 Restrictions Not available for BMaSc or BMaSc(Adv) students or BMaSc (Hons) [Direct Entry] Assessment On-going assessment, exam Course Staff
Course Coordinator: Dr Stuart Johnson
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
On successful completion of this course students will be able to:
1. Demonstrate understanding of basic mathematical concepts in data science, relating to linear algebra, probability, and calculus.
2. Employ methods related to these concepts in a variety of data science applications.
3. Apply logical thinking to problem-solving in context.
4. Use appropriate technology to aid problem-solving and data analysis.
5. Demonstrate skills in writing mathematics.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
all Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
3,4,5 -
Learning Resources
Required Resources
All required resources are provided in MyUni.
There is no requirement to buy a textbook.Recommended Resources
- Lay: Linear Algebra and its Applications 4th ed. (Addison Wesley Longman)
- Stewart: Calculus 7th ed. (international ed.) (Brooks/Cole)
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Learning & Teaching Activities
Learning & Teaching Modes
This course uses a flipped learning model, the course materials are contained in modules on MyUni with a mix of text, videos and exercises to work through each week.
In addition we have a weekly seminar including interactive exercises to support your learning of this material as well as alternating
practical and workshop classes to provide students with class/small group/individual assistance. There are computer based quizzes and written assignments to provide formative assessment opportunities for students to practice techniques and develop their understanding of the course.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload hours Course Notes & Videos 1 set 78 Seminars 12 12 Workshops 6 6 Practicals 6 6 Mid Semester Tests 1 6 Assignments/Quizzes 6 48 Total 156 Learning Activities Summary
Course Content Outline
Fundamentals (weeks 1-2)
- Approximation
- Sets and Functions
- Sums
Probability (weeks 3-4)
- Counting
-Conditional probability
- Bayes theorem
- Discrete random variables
Applications of Calculus (weeks 5-6)
- Integration and continuous probability distributions
- Series Approximations
Representing Data with Matrices (weeks 7-8)
- Matrix operations
- Matrix equations
- Determinants
Solving Linear Equations (weeks 9-10)
- Row reduction
- applications
- linear independence
Eigenvalues and Dimensional Reduction (weeks 11-12)
- Eigenvalues and eigenvectors
- Diagonalisation and Dimensional reduction
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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
Component
Number
Timing
Weighting CLOs Assignments 6 Due in weeks 3,5,7,9,11,13 20% All Quizzes 6 Due in weeks 3,5,7,9,11,13 10% 1,2,3,4 Mid Semester Test 1 During Week 6 10% 1,2,3,4 Exam 1 During Exam Period 60% 1,2,3,5 Assessment Related Requirements
An aggregate score of 50% is required to pass the course. Furthermore students must achieve a grade of at least 40% on the final exam in order to pass the course.Assessment Detail
Quizzes are short answer questions done on Mobius which is accessed online. They can be completed at any time before the due date, and can be reattempted as many times as required.
Assignments involve longer written answers which are submitted online for marking. They are graded according to correctness of mathematics and clarity of presentation, using appropriate mathematical language and notation in implementing techniques presented in the course.
The Mid-semester Test is a closed book, invigilated test conducted in the scheduled Assessment class in a computer lab.
The final exam is a closed book, written exam.Submission
- All written assignments are to be e-submitted following the instructions on MyUni.
- Written Assignments are accepted up to 24 hours after the due date with no penalty, no submission is possible after that time unless a student has applied for an extension under the conditions of the Modified Arrangements For Coursework Assessment (MACA) Policy.
- Quizzes may be worked on, with instant feedback avialable up until the due date, with answers saved as it is worked on, so no late submission is possible, work completed by the due date is accepted, unless an extension is granted under MACA Policy.
- Written assignments will have a one week turn-around time for feedback to students.
- Feedback on the mid-semester test will be released as soon as possible when all students have completed it.
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
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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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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Fraud Awareness
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.
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