Mathematics Essentials in Data Analytics
UndergraduateUSA-MATH10812025
Course information for 2025 intake
Enrol today with instant approval and no entry requirements
- Study method
- 100% online
- Assessments
- 100% online
- Enrol by
- 5 Jan 2025
- Entry requirements
- No ATAR needed, No prior study
- Duration
- 10 weeks
- Start dates
- 13 Jan 2025,
- 30 June 2025
- Price from
- $2,300
- Upfront cost
- $0
- Loan available
- HECS-HELP and FEE-HELP available
Mathematics Essentials in Data Analytics
About this subject
By the end of this 10-week course, you’ll be able to:
- Demonstrate working knowledge of linear algebra, including vectors and matrices to solving problems.
- Apply selected optimisation techniques in the context of data analytics.
- Apply probability concepts and statistical methods to solving data analytical problems.
- Communicate results of mathematical modelling in context of data analytics.
- Introduction to vectors and matrices
- Eigenvalues and Eigenvectors
- Grad, Diff and Linear Regression
- Gradients & Optimisation
- Applications to Data Analytics
- Introduction to Probability Theory & Bayes Theorem
- Probability Distributions and Simulations in R
- Central Limit Theorem and Confidence Intervals
- Statistical Inference
Gain a solid foundation in mathematical and statistical concepts essential for mastering data analytics.
This course covers key topics such as linear algebra concepts, vector and matrix operations, and the fundamentals of eigenvalues and eigenvectors. Explore dynamical systems and optimisation techniques, including gradient descent. Dive into linear regression, probability concepts—such as probability laws, Bayes' rule, and independence—and selected probability distributions. Learn the principles of statistical inference and how to apply them effectively to data analytics.
This is a first-year course from UniSA Online’s Data Analytics degree. When studying this course as a "single subject", prior knowledge from MATH 1080, MATH 2032 or equivalent will support your success.
Delivered 100% online, you’ll be able to study where and when it suits you. Access online academic and student support seven days a week, fit study around work and life commitments, view learning resources 24/7, and log in to the interactive online environment anywhere, any time and on any device.
Should your course have an exam it will be scheduled for Australian Central Standard Time or Australian Central Daylight Time, depending on the time of the year.
- Continuous (Problem solving exercise) (40%)
- Continuous (Project) (60%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
No entry requirements
Additional requirements
- Other requirements - Students must be aged 17 or older by the time teaching commences for their course of study, in accordance with UniSA’s Selection and entry to programs policy.
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.
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Most single subjects are part of a full degree. That means if you’re keen to keep learning, you can gain credit for the subjects you’ve successfully completed.
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Each of your subjects will be held over the course of a study term, and they’ll usually require 10 to 12 hours of study each week. Subjects are identified by a title and a code, for example, Developmental Psychology, PSY20007.
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If that degree allows entry via undergraduate subjects, there will be information about this under the Entry Requirements section. You will find a list of 2-4 open enrolment subjects you need to successfully complete to qualify for admission into that qualification.
Once you pass those subjects, you will satisfy the academic requirements for the degree, and you can apply for entry.
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