Applied Data Analytics

Both industry and government in general faces a current and prospective challenge in recruitment, developing and retaining workforce with skills in data analytics as employed to high-quality, data-informed decisionmaking. This program is multi disciplinary comprising of computer science and applied statistics for graduate-level reskilling and upskilling within the field of employed analytics that can be implemented across a multitude of settings in the health to national security. The program is design to provide student with experience of best practice in data analytics, and cuttingedge courses in areas of significance to data analytics practitioners and opportunities to deepen awareness in a number of the 3 areas of computation, statistics or science.

Program Overview: Applied Data Analytics at The Australian National University

The Applied Data Analytics program at The Australian National University (ANU) offers students a comprehensive education in the skills and knowledge necessary to analyze, interpret, and leverage complex data sets across various industries. Designed to equip graduates with both theoretical foundations and practical expertise, this program prepares students to meet the growing demand for data-driven decision-making in today's digital economy.

Curriculum Content

The program covers a wide range of topics essential for proficient data analytics professionals. Students begin with foundational courses in statistics, mathematics, and programming, focusing on languages such as R and Python, which are integral tools in data analysis. Building upon this base, the curriculum explores data management techniques, including database design, data warehousing, and SQL, ensuring students can effectively collect, store, and retrieve large volumes of data.

Advanced coursework delves into machine learning, predictive modeling, and artificial intelligence, enabling students to develop algorithms that uncover patterns and generate insights from complex datasets. The program emphasizes practical applications through hands-on projects, case studies, and collaborations with industry partners, allowing students to solve real-world problems in sectors like finance, healthcare, government, and technology.

Ethics and Data Governance

Recognizing the importance of ethical considerations in data analytics, the program incorporates modules on data privacy, security, and ethical use of data. Students learn about legal frameworks and best practices to responsibly handle sensitive information and ensure compliance with data protection regulations.

Capstone Project

A key component of the Applied Data Analytics program is the capstone project, where students apply their accumulated knowledge to a substantial, real-world data challenge. Working in teams or individually, students demonstrate their ability to analyze data, develop models, interpret results, and communicate findings effectively to stakeholders.

Career Opportunities

Graduates of the program are well-prepared for diverse roles such as data analyst, data scientist, business intelligence analyst, and analytics consultant. The skills acquired also enable career advancement into management positions overseeing data projects, or further study in specialized fields like machine learning and AI research.

Program Goals

The objective of this program is to produce graduates who are proficient in the technical aspects of data analysis, possess a strong understanding of data ethics, and can apply their skills across various sectors to drive strategic decisions and innovation. With the increasing importance of data in industry and government, this program aims to contribute to building a workforce capable of transforming data into actionable insights.

Duration, Entry Requirements, and Delivery Mode

The program typically spans one year of full-time study or equivalent part-time. Entry requirements include an undergraduate degree in a relevant discipline such as computer science, statistics, or engineering, along with mathematical and programming competencies. The program is delivered through a combination of lectures, tutorials, practical sessions, and industry placements, available on campus and online to accommodate diverse student needs.

Join the Applied Data Analytics program at ANU and be at the forefront of data innovation, turning complex data challenges into meaningful solutions that shape the future of various industries worldwide.

• Entry requires a licensed Honours or Bachelor degree, or international equivalent with minimum GPA of 5.0/ or 7.0, also three decades of work experienceequivalent. Cognate areas: Engineering
• Maths, Physics
• Statistics, Finance
• Actuarial Studies
• Compsci
• I T
• Criminology
• Sociology
• Political
• Science
• Behavior
• Epidemiology/Public Health
• Anthropology
• Demography/Population Studies.

The Master of Applied Data Analytics at the Australian National University (ANU) offers a range of financing options to support students throughout their studies. International students are required to pay tuition fees, which vary depending on the specific program structure and year of enrollment. ANU provides detailed information about tuition costs on their official website, and students are advised to check the latest figures before applying. For domestic students, the program may be subsidized under the Australian Government’s Higher Education Loan Program (HELP), which allows eligible students to defer their tuition fees and repay them through the tax system after graduation. This financial assistance aims to reduce upfront costs and make higher education more accessible. Additionally, ANU offers scholarships specifically tailored for students enrolling in data analytics or related fields. These scholarships are competitive and typically awarded based on academic merit, leadership qualities, or financial need. Some of these are offered directly by the university, while others are funded by external organizations or industry partners. International students are encouraged to explore scholarship opportunities, which may include destination-specific awards, excellence scholarships, and country-specific grants, all aimed at reducing the financial burden. Besides scholarships and government schemes, students can also consider external funding sources such as private loans, employer sponsorships, or sponsorships from industry organizations involved in data science and analytics. It’s important for prospective students to carefully review the eligibility criteria, application deadlines, and application procedures for each funding option. ANU’s financial advisory services are available to help students understand their options and plan their finances effectively. Additionally, students may explore part-time work opportunities available on campus or in the nearby Canberra area to supplement their income during their studies. Overall, the ANU seeks to provide comprehensive financial support mechanisms and guidance to ensure that students pursuing the Master of Applied Data Analytics can focus on their studies and career development without undue financial stress.

The Master of Applied Data Analytics at the Australian National University (ANU) is a postgraduate degree designed to equip students with advanced skills in data analysis, statistical modelling, and machine learning techniques applicable across a broad range of industries. The program aims to address the increasing demand for data-savvy professionals capable of interpreting complex data sets to inform decision-making, optimize processes, and generate innovative solutions. Delivered primarily at the ANU Research School of Finance, Actuarial Studies and Statistics, this program combines theoretical foundations with practical application, ensuring graduates are well-prepared for careers in government, finance, healthcare, technology, and consulting sectors. Coursework involves a combination of programming, data management, statistical inference, and predictive analytics, with opportunities for students to undertake applied projects and industry placements. The program emphasizes the development of skills in using tools such as R, Python, and SQL, along with training in visualisation techniques and ethical considerations related to data use. It caters to individuals with a background in quantitative disciplines such as mathematics, statistics, computer science, or related fields, aiming to deepen their expertise and broaden their career prospects. The duration of the program is generally one and a half to two years for full-time students, with options for part-time study. Entry requirements typically include a relevant undergraduate degree and evidence of quantitative ability. Graduates of this program are prepared for roles such as data analysts, data scientists, business analysts, and researchers in various sectors, contributing to data-driven decision making and policy development. The ANU’s strong links with industry and government ensure that the curriculum remains current and responsive to emerging trends in data analytics.