Open Universities Australia

Student Hub home

Plan and enrol

Statements

Manage your studies

Manage your account

Study essentials

Key dates

Access LMS

Get support

Architecture & construction

Art & creative design

Business & management

Community services & care

Education & teaching

Engineering

Health & medical science

Humanities & social science

IT & computer science

Law & justice

Media & communication

Psychology & mental health

Science

Search all courses

Explore study online

Undergraduate degrees

Postgraduate courses

University certificates

Pathways and pre-university

Single subjects

Microcredentials

Short courses

Study types

Help me choose a course

Chat with a student advisor

Compare courses

Degrees vs single subjects

Choosing a course

Study online

How OUA works

How to enrol

RPL and credit

Study planning

Minimum age requirements

Textbooks & study materials

Computer requirements

International students

Getting started

Student loans

Study allowances

Commonwealth supported places

Fees

Financial options

Disability support

Elite athletes

Exams

Natural disaster support

Special Circumstances

Study preparation

Student support

Support

Your studies

Advice

13 6736

Study Master of Data Science online through Open Universities Australia. Explore all degrees, subjects and short courses now.

Public health is a broad field which aims to improve and protect the health and well-being of the general population. As a public health practitioner, you can make a real difference to the lives of local, national and international communities.Public health practitioners help individuals and communities to have greater control over their health and well-being, and to influence organisational and political environments in ways that lead to better health for all. They work across the lifespan, including the early years, child and adolescent health, and healthy aging to support population health.We realise that public health is such a broad area, which is why this masters degree offers a variety of elective units to allow you to specialise in an area of interest. You will also work closely with public health industry professionals and complete research projects on current issues in public health, which will help form a personal portfolio of evidence to support your transition into the profession.Students have the option of studying this course on-campus or online.

Protect the community against diseases with a career in the public health sector. Discover how to gather data and conduct essential clinical research. Focus on an area that interests you, like adolescent health, nutrition or epidemiology.

Master of Public Health

The Master of Management is designed in consultation with our network of industry and professional partners. It is informed by world-class research in management, marketing and business, combining up-to-date theory and the practical application of management models and methods.With flexible learning arrangements to best suit your individual needs, this degree is delivered face-to-face, 100% online or as a combination of both. There are a range of options available to fast track your learning.One of only ten in Australia with EQUIS accreditation, UniSA Business is ranked in the top one per cent worldwide1. EQUIS is the world’s leading international accreditation for business schools, awarded by the quality assurance arm of the European Foundation for Management Development (EFMD).UniSA Business is the only business school in South Australia accredited by both AACSB International (The Association to Advance Collegiate Schools of Business) and EFMD (EQUIS) – the world’s leading accreditation bodies recognising excellence in business education and research at a global level. These dual accreditations demonstrate the high standards we hold across all areas such as teaching, student learning and research, as well as our commitment to continually improving the quality of our programs. 1UniSA Business is one of just 13 institutions in Australia and approximately 200 globally (from over 25,000 universities) to be EQUIS accredited. EFMD, March 2024. 2023 QS Stars Business School Ratings.

Learn contemporary marketing strategies, essential management skills and specialised areas including data analytics. You’ll explore buyer behaviour, business ethics and more. Gain the expertise to achieve business marketing objectives in any industry.

Master of Management (Marketing)

This program provides students with a broad range of knowledge, skills and resources to practise effectively as a clinical pharmacy practitioner involved in the quality use of medicines and pharmaceutical care. These skills include the capacity to individualise, review and monitor a patient&#39;s medication regimen; demonstrate effective communication skills in clinical and non-clinical scenarios; critically appraise medical and pharmaceutical literature, as well as to recognise and describe social issues relating to medicine use.In addition pharmacists will gain insight into contemporary management strategies for pharmacy and health care as well as explore research and evaluation of pharmacy services and practice.Regular updates of the program integrate emerging clinical evidence and current controversies. A major strength of the program is the emphasis on developing clinical practice and the integration of evidence based medicine.

Focus on evidence-based, patient-centred care. You’ll explore up to date management and optimisation of pharmacotherapy. Gain skills to provide positive patient outcomes within a complex health environment. Taught by world-leading teachers.

Master of Clinical Pharmacy

Scientific Computing

Introduction to Spatial Information

From Logic to Data Processing

Database for the Enterprise

Data and Analysis

Data Analytics Concepts

Business Intelligence

Data Analytics for Cyber Security

Data Visualisation

Data-Based Critical Thinking

The world now runs on data. If knowledge is power, data science is increasingly how we discover that knowledge. With limitless possibilities for exploration and innovation, it is a field driven by discovery and communication. This subject introduces you to data science using simple and efficient toolkits in Python. You will explore various datasets and apply machine learning algorithms to them. In doing so, you will gain an understanding of data processing workflows, exploration, and visualisation, as well as a conceptual understanding of many of the algorithms themselves. Designed to be exploratory and collaborative, the subject offers you invaluable insights into a rapidly evolving field with diverse and increasingly important applications.

Data Science Studio 1

Equip yourself with the skills to effectively interact with large structured and unstructured data sets in our comprehensive course.Explore critical topics such as concurrency and transaction management, data organisation, hashing, indexing, and query optimisation. Learn about active databases and procedures, distributed database design, fragmentation, and replication. Master the intricacies of distributed transactions and delve into the architecture and components of data warehouses.Understand data warehouse modelling, including star and snowflake schemas, and gain proficiency in multidimensional Online Analytical Processing (OLAP) and relational OLAP analysis. Learn to design data warehouses and manage data uploading, updating, and integration.UniSA Online’s 10-week short courses give you the flexibility to up-skill in a certain area, stay current with developments in your field, diversify your knowledge, or even explore a new direction in your career – without having to commit to the time and cost of a full university degree.  This is a second-year course from UniSA Online’s Bachelor of Data Analytics. When studying this course as a &quot;single subject&quot;, prior knowledge from INFT 1032 , INFT 1025 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.

In an era of rapid technological innovation, data and the capacity to process it are the most valuable assets in many fields. Studying this subject, you will learn how data is represented, stored and processed in computer systems. Extending your high-level technological literacy, the subject introduces you to a way of thinking that uses abstraction to move from low level hardware concepts to higher level programming concepts. Working through the natural progression of related concepts in computer programming, you will first explore how circuits can implement logic, then how logic lets us implement computer architecture (memory, processors), and how assembly language lets us write programs that manipulate data, before circling back to the relationship between programs and logic.

Get an introductory understanding of the links between logic, reasoning, data, and computation. Learn how data is represented, stored, and processed in computer systems. 

This subject introduces essential concepts and techniques of computing for conducting science, with special emphasis on the preparation and manipulation of data. We discuss the role of computers and computing tools in science and focus on the use of spreadsheets and other data manipulation tools. Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (<a href="https://sdgs.un.org/goals" target="_blank">UNSDG</a>s) Industry, Innovation and Infrastructure

Build data and IT skills that you’ll use throughout your science degree and career. You’ll learn how to collect, prepare, and process data using computers. See how spreadsheets can enhance the efficiency and accuracy of your scientific research.

This subject is designed to give students a general overview of spatial information and its applications. Spatial information is becoming an increasingly prevalent part of our daily lives. The ability to incorporate spatial information into various applications is a valuable skill, with applications across all manner of disciplines and vocations. This subject will introduce students to Geographic Information Systems (GIS) using ESRI ArcGIS Pro. In this subject, students will learn the fundamental concepts underpinning spatial information, and how to represent a variety of variables in a spatial way. Content in this subject is technical in nature, although delivered at the introductory level for students who may be curious about the potential of spatial information, and want to develop a basic skillset to analyse and interpret datasets. Concepts that will be introduced include: spatial referencing systems, types of spatial data, creating new datasets, basic vector analysis, and data visualisation through maps.

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&#39; 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 &quot;single subject&quot;, 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.

Mathematics Essentials in Data Analytics

Build a strong mathematical foundation for your data analytics journey with our comprehensive course.Explore essential topics including arithmetic and algebraic operations, linear and quadratic equations, and logarithmic and exponential functions. Dive into matrices and determinants, and master absolute values, inequalities, and sets. Gain a solid grounding in basic probability and statistics to support your data analytics skills.Join us to develop the mathematical skills needed to excel in data analytics and unlock new opportunities for data-driven insights!This is a first-year course from UniSA Online’s Data Analytics degree. 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.

Fundamentals of Mathematics for Data Analytics

Enhance your skills in applying supervised, unsupervised, and deep machine learning techniques to solve real-world data analytics challenges.In this course, you&#39;ll explore linear regression, regularisation, and logistic regression, and delve into advanced neural network architectures and learning techniques. Gain expertise in convolutional and recurrent neural networks, including long short-term memory (LSTM) networks. Learn practical applications of machine learning, including clustering, dimensionality reduction, anomaly detection, and large-scale machine learning.UniSA Online’s 10-week short courses give you the flexibility to up-skill in a certain area, stay current with developments in your field, diversify your knowledge, or even explore a new direction in your career – without having to commit to the time and cost of a full university degree.  This is a third-year course from UniSA Online’s Data Analytics degree. When studying this course as a &quot;single subject&quot;, prior knowledge from INFS 3081, INFS 3076 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.

Machine Learning

In this subject, you will be introduced to mathematical and statistical methods for analysing scientific, business or technical data to inform and support decision-making. You will explore why data is needed and how it is used to make decisions, including how data are collected, analysed, interpreted and presented, and you will learn and apply a suite of common statistical and mathematical methods to generate evidence for decision-making.You will also be introduced to data management software and learn how to represent and communicate mathematical and statistical information effectively. Through data sets relevant to your discipline, you will learn how to problem solve, generate evidence, and present solutions using data handling and statistical approaches.

Any modern business today will utilise some form of spreadsheet tool to review, manipulate and visualise data (in the form of charts for reporting). A spreadsheet tool also enables one to undertake advanced tasks on business data, such as performing scenario analyses and undertaking complex data analytics, for example creating a forecasting model. In this subject, you will learn how to use two technological tools to undertake data analysis. The first tool is Structure Query Language (SQL), which we will use to pull relevant data into Excel and facilitate further analysis. Next, various advanced Excel analyses including pivot tables, statistical analysis, and creation of basic forecasting models will be covered. Upon successful completion of this subject you will be proficient in basic data analysis using Excel and SQL, setting you up to become an analytical and data driven problem solver. With these skills, you will also be ready to identify insights allowing you to disrupt typical business operations systematically and with a higher chance of success.

Get up to speed with basic data analysis using SQL and Excel. You’ll delve into the data analytics concepts and processes used in business today. Find, present, and explain data trends. Solve complex business problems.

Master of Data Science Courses & Degrees | Open Universities Australia

Search thousands of courses and degrees by leading Australian universities

Course results for Master of Data Science

Need help choosing a course?

Related searches

Keep track of your favourites

Create an account