Science
Master of Data Analytics
Learning Mode
Full Time
Duration
2 Years (4 trimesters) full-time
Start date
March, July, November
Qualification
Master of Data Analytics
Fees
PG – 24,768 AUD for 1 yr full-time
Location
Melbourne / Sydney
About the Course
The Master of Data Analytics (MDA) at Melbourne Institute of Technology (MIT) offers an advanced and highly practical postgraduate program designed for graduates and professionals seeking to become experts in the field of data analysis. This program provides comprehensive knowledge and advanced skills in data collection, processing, statistical modelling, machine learning, and data Visualisation using industry-standard tools. You will learn to extract meaningful insights from complex and large datasets, develop predictive models, and inform strategic decisions, preparing you for leadership roles in various data-driven industries, particularly in emerging areas like artificial intelligence, deep learning, and smart technologies.
Career prospects
Graduates of the Master of Data Analytics program are highly sought after across diverse industries, including technology, finance, healthcare, retail, government, and consulting, both in Australia and internationally. The program prepares students for specialized and leadership roles such as Data Scientist, Senior Data Analyst, Business Intelligence Developer, Machine Learning Engineer, Data Architect, and Quantitative Analyst. Our strong emphasis on practical application, advanced analytical techniques, and real-world problem-solving ensures graduates are well-equipped for impactful and evolving careers in the data-driven economy.
Why choose Melbourne Institute of Technology for a Master of Data Analytics?
Industry connected
Gain real-world experience through projects and guest lectures with leading data-driven companies and professionals.
Global opportunities
Study global trends and technologies, preparing for advanced analytics roles across international data-driven industries.
Professional accreditation
TEQSA-accredited and aligned with ACS standards, enhancing employability and recognition in the data analytics profession.
Course Overview
The Master of Data Analytics program at Melbourne Institute of Technology offers a dynamic and engaging learning experience, designed to develop highly skilled and innovative data professionals at an advanced level. The curriculum integrates advanced concepts from data science, statistics, artificial intelligence, and machine learning, with a strong emphasis on their practical application. Students will gain advanced expertise in data visualization, statistical analysis, predictive modelling, and strategic decision-making using a suite of industry-standard software and programming languages including Tableau, Python, R, SQL, NoSQL, and MATLAB. The program includes an Industry-based Project where students apply their learning to complex real-world challenges, fostering creative thinking, communication, and leadership skills crucial for success in this evolving industry.
Course Duration
Length of the course
- 2 years full-time (4 trimesters)
Mode of Study for international students:
- Full-time (on-campus)
Course Curriculum
The Master of Data Analytics curriculum is structured to provide a comprehensive and advanced understanding of data analytics principles, tools, and applications, culminating in significant project work.
- Core Data Analytics & IT Fundamentals:
- Includes foundational units like Data Science Principles, Advanced Programming, Database and Web Technologies, Cloud Computing, and Information and Network Security.
- Advanced Analytics & AI:
- Deep dives into areas such as Advanced Data Analytics, Applied Artificial Intelligence, Machine Learning, Deep Learning, and Smart Industry Automations.
- Research & Project Work:
- Includes units on Research Methods and a substantial Industry-Based Project or Research Thesis, where students apply their advanced knowledge to solve complex data problems for real clients or engage in cutting-edge research.
- Electives:
- Students may choose electives from a range of advanced IT or business topics to further specialize their skills.
Admission Requirements
- Academic qualifications
- A Bachelor’s degree (AQF Level 7 equivalent course) in an IT or quantitative discipline from a recognized university.
- OR, a Bachelor’s degree in a non-IT discipline with relevant professional work experience (typically 2+ years in an IT-related role) or demonstrable quantitative aptitude.
- OR, a Graduate Certificate or Graduate Diploma in a relevant IT or quantitative field.
- Prior learning recognition
- Recognition of prior learning (RPL) may be available for relevant previous postgraduate study or extensive professional experience, potentially reducing the course duration.
Language Proficiency
- English language requirements (e.g., IELTS, TOEFL)
- The minimum score required is an overall IELTS (Academic) band score of 6.0, with no individual band score less than 5.5, or equivalent scores such as PTE Academic (overall 50, with no section less than 42) or TOEFL iBT (overall 60-78, with minimum scores: Reading 12, Listening 11, Speaking 17, Writing 20).
Fees and Funding
Tuition Fees:
- PG – 24,768 AUD for 1 yr full-time
Scholarships and Bursaries:
- Melbourne Institute of Technology may offer various scholarships and bursaries for postgraduate students, including “Beyond the ATAR” scholarships (for domestic) and potentially international student scholarships. Prospective students are encouraged to check the MIT website for any available opportunities or payment plan options.
Career Opportunities
Graduates of the Master of Data Analytics program are highly versatile and prepared for leadership and specialized roles in the data-driven economy. Potential job roles include Data Scientist, Senior Data Analyst, Business Intelligence Developer, Machine Learning Engineer, Data Architect, Big Data Engineer, Quantitative Analyst, AI Specialist, Consultant (Data & Analytics), and Chief Data Officer (with experience). Industries employing our graduates span technology, finance, health, science, law, government, retail, manufacturing, and any sector leveraging big data for strategic decision-making, innovation, and competitive advantage, both domestically and internationally.
Contact Us
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