James Cook University
Master of Data Science (Professional)
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
Across recent developments and modern challenges in data science and equipped with skills in key areas including machine learning, data mining, algorithm development, and advanced modelling.
Course overview
JCU students have the advantage of learning how to apply data science skills to tropical, regional, and Aboriginal and Torres Strait Islander contexts. Benefit from industry expertise with courses taught by data scientists, SAS partnership and certification, and access to the SAS data Science Academy.
Learn to exercise your professional judgment to suit specific circumstances and have the opportunity to complete a substantial research-based project. Your capstone project will allow you to build a portfolio to showcase your expertise.
Key facts
Cairns, City
November, 2025
What you will study
To complete the Master of Data Science (Professional), you must earn 36 credit points.
- Foundations for Data Science
- Statistical Methods for Data Scientists
- Data Visualisation
- Database Systems
- Programming and Data Analytics using Python
- Career Planning
- Introduction to Data Mining
- Visual Analytics for Data Scientists using SAS
- Data Science Master Class One
- Advanced Data Management and Analysis using SAS
- Professional Placement/Internship One
- Data Science and Strategic Decision Making for Business
- Data Information: Management, Security, Privacy and Ethics
- Data Science Master Class Two
- Data Mining and Machine Learning
- Professional Placement/Internship Two
Entry requirements
Mathematics B (or equivalent that includes algebra and elementary differential calculus) together with some background in computing, data analysis or programming is assumed. Admission based on relevant industry experience must be supported by a detailed CV and proof of work experience (e.g. a letter from an employer detailing the position and job description).
- Completion of an AQF level Seven bachelor degree.
- Five (5) years or more relevant industry experience in IT or Data Science/Data Analytics.
- Other qualifications or practical experience recognised by the Dean, College of Science and Engineering as equivalent to the above.
Entry requirements for this course are consistent with the Pathways to Qualifications in the Australian Qualifications Framework (AQF level Nine) Guidelines for Masters degrees.
Applicants of non-English speaking backgrounds must meet the English language proficiency requirements of ”Band 2” – Schedule II of the JCU Admissions Policy.
Outcomes
Learning outcomes
- Integrate and apply an advanced body of practical, technical, and theoretical knowledge, including an understanding of recent developments and modern challenges, in Data Science and its application.
- Retrieve, analyse, synthesise and evaluate complex information, concepts, methods, or theories from various sources.
- Plan and conduct appropriate investigations of data sets by selecting and applying qualitative and quantitative methods, techniques and tools, as appropriate to the data and the application.
- Analyse requirements, and demonstrate effective applications of appropriate computing languages and computational tools for data acquisition, queries, management, analysis and visualisation.
- Identify, analyse and generate solutions for complex problems, especially related to tropical, regional, or Indigenous contexts, by applying knowledge and skills of data science with initiative and expert judgement.
- Communicate data concepts and methodologies of data science, as well as the arguments and conclusions of the application of data science, clearly and coherently to specialist and non-specialist audiences through advanced written and oral English language skills and a variety of media.
- Critically review ethical principles, issues of data security and privacy, and, where appropriate, regulatory requirements and cultural frameworks to work effectively, responsibly and safely in diverse contexts.
- Reflect on current skills, knowledge and attitudes to manage their professional learning needs and performance autonomously and/or in collaboration with others
- Apply knowledge of research principles, methods, techniques and tools to plan and execute a substantial research-based project, capstone experience and/or piece of scholarship.
Career outcomes
Graduates benefit from rapidly increasing job openings across the data industry and a data-driven future. You can apply data science to industrial, environmental, cultural, societal, and agricultural projects.
You could find work as a:
- Data Scientist
- Data Engineer
- Data Analyst
- Data Architect
- Visualisation Specialist
- Statistician.
Fees and FEE-HELP
Estimated annual tuition fee (2025): $31,701 (domestic full-fee paying place)
Student fees may vary in accordance with:
- The number of units studied per term.
- The choice of major or specialisation.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees shown are subject to change. Contact the university directly to confirm.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.