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Study associate degree online through Open Universities Australia. Explore all degrees, subjects and short courses now.

Gain an industry-recognised qualification in just two years and jump-start your data analytics career with Adelaide University’s 100% online Associate Degree in Data Analytics. Whether you’re starting out or looking to upskill, learn the latest industry tools and graduate ready to step into a dynamic and growing field.Develop the skills to turn raw data into powerful insights, and learn how to collect, manage, and analyse information to help any organisation grow and thrive. Discover how to use the latest tools and techniques for data cleaning and data acquisition, and how to select data and algorithms to generate insights.Learn problem-solving, maths, and statistics, and apply your knowledge in simulated work environments. Explore real-world case studies and experience what it’s like to work as a data analyst. Get up to date with the latest technology and software, ready to succeed when you graduate.

Launch your data career in just two years. You’ll cover programming, database design, and data analysis. Explore real-world case studies and gain hands-on experience. Graduate job-ready for entry-level roles – or continue to study with credit.

Associate Degree in Data Analytics

Data and Analysis

Data Analytics Concepts

Business Intelligence

Scientific Computing

Data Analytics for Cyber Security

Data Visualisation

Data-Based Critical Thinking

HR Analytics

Professional Practice in Data Analytics

Disruption in Business

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

This subject introduces students to the theory and practice of information design, displaying data with purpose to foster understanding and engagement. Using a variety of sources, students identify and collate quantitative and qualitative data before synthesising and analysing it with applied organisational methods. Using visualisation techniques, students bring the information to life by telling its story in graphic and/or interactive form that represents the data in an effective and compelling way.

Turn complex data into clear, engaging visuals that tell powerful stories. You’ll learn how to organise, analyse, and visualise data in ways that inform, inspire, and influence audiences.

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.

Note: If you study this subject in Winter, the subject will be a shorter duration (5 weeks) and will require at least 20 hours of study per week. Summer also has a shorter duration (9 weeks).Data analytics is present in every moment of our lives. Data flows through smart phones, smart cars, smart fridges, streaming services, social media, loyalty programs, business operations, logistics, leisure and entertainment like a current shaping everything. At the heart of comprehensive data collection and analysis is a quest to understand ‘everything’, and this unit invites students into this multi-layered data-driven world. MSP202 teaches students how to clean, manipulate, and transform data into creative visualisations using Microsoft Excel to tell a data-driven story for invested stakeholders. Students examine the impact of data analytics in the context of public and personal life, professional and industry domains, and the reach of data across local, national, and global contexts. This unit explores ethical issues relating to data surveillance, the implications of data mining on human behaviour, and the analytics machines central to the functioning of big tech platforms such as Google, Amazon, and Facebook. The unit offers students skills development to engage with data with an awareness of ethical considerations, and the capacity to manipulate that data to make sense of it for invested stakeholders, telling a story that has the capacity to change the world.Please Note: All students studying at Murdoch University will need to complete the compulsory unit, Murdoch Academic Passport (MAP100), which only takes 2-3 hours to complete online. Find out more: <a href="http://goto.murdoch.edu.au/MurdochAcademicPassport" target="_blank">http://goto.murdoch.edu.au/MurdochAcademicPassport</a>

Work with data and see the impact you can have on everyday life. From collection to analysis, you’ll explore how data tells stories, informs decisions, and influences human behaviour. Get creative with visualisation. Get ethical with your approaches. 

The Search for Everything: data Analytics and Storytelling in the 21st Century

This subject introduces students to modern data analytics, visualisation, and statistics. It equips students with the skills required to take advantage of powerful computing for the analysis and visualisation of complex data. These skills are used to solve problems in areas such as the biological sciences, medical sciences, agricultural sciences, nutrition, health sciences, education, and business. Students will become familiar with data visualisation and computing, descriptive statistics, statistical modelling, and data-based decision making. Using statistical computing packages is an integral part of this subject. This subject allows further study in second-year subjects in statistics and data science.

Making Sense of Data

In this subject, you are introduced to quantitative statistics, qualitative coding and the role of health data analytics in healthcare organisations and public health research. Key emphases include understanding the importance of healthcare data as an asset, identifying and applying the key elements of the data capture and analysis process in key research methodologies, along with effective presentation, communication and dissemination of findings beyond peer review publications. You will also investigate the role of health data analytics in quality and performance indicators. This subject includes synchronous sessions held during business hours. This means that you will attend sessions each week simultaneously with your facilitator and classmates. This subject is recommended for first-year undergraduate students.

Introduction to Data Analytics in Healthcare

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 (UNSDGs) 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.

Associate Degree Data analytics Courses & Degrees | Open Universities Australia

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