Bachelor of Information Technology and Master of Data Science

Macquarie University

About

Overview The Bachelor of Information Technology and Master of Data Science provides graduates with the necessary skills to pursue a high-level career in Information Technology with a focus on Data Science, including advanced material at the postgraduate level.

A foundation of programming, data, networking and cyber security provides a solid base … For more content click the Read More button below.

The emphasis is on concepts, insights and skills that enable graduates to use current technologies and to also evaluate and adapt to new technologies as they emerge.

Central to the learning of the conceptual material is extensive practical experience where non-trivial problems are analysed, solutions designed and developed, both individually and in groups.

A final-year undergraduate industry-based group project in the PACE/capstone unit brings everything together to solve a real world problem.

In the transition third year, students study a mixture of advanced undergraduate Data Science, including statistics, and build on their undergraduate knowledge and skills with the beginning of postgraduate study.

The fourth year comprises advanced postgraduate courses in Data Science, including a (20cp) capstone project that can be either an industry placement (internship) or internal research project.

This allows students to gain experience working on real Data Science projects and, for appropriate students, direct exposure to industry problems and practices.The Bachelor of Information Technology and Master of Data Science provides graduates with the necessary skills to pursue a high-level career in Information Technology with a focus on Data Science, including advanced material at the postgraduate level.

A foundation of programming, data, networking and cyber security provides a solid base for later study.

The Data Science major from the Bachelor of Information Technology provides foundational undergraduate study in the area.

The emphasis is on concepts, insights and skills that enable graduates to use current technologies and to also evaluate and adapt to new technologies as they emerge.

Central to the learning of the conceptual material is extensive practical experience where non-trivial problems are analysed, solutions designed and developed, both individually and in groups.

A final-year undergraduate industry-based group project in the PACE/capstone unit brings everything together to solve a real world problem.

In the transition third year, students study a mixture of advanced undergraduate Data Science, including statistics, and build on their undergraduate knowledge and skills with the beginning of postgraduate study.

The fourth year comprises advanced postgraduate courses in Data Science, including a (20cp) capstone project that can be either an industry placement (internship) or internal research project.

This allows students to gain experience working on real Data Science projects and, for appropriate students, direct exposure to industry problems and practices.Read More

Entry requirements

About inherent requirementskeyboard_arrow_down

Inherent requirements are the essential components of a course or program necessary for a student to successfully achieve the core learning outcomes of a course or program. Students must meet the inherent requirements to complete their Macquarie University course or program. For more information see https://students.mq.edu.au/study/my-study-program/inherent-requirements. Inherent requirements for Macquarie University programs fall under the following categories:

Physicalkeyboard_arrow_down

The physical inherent requirement is to have the physical capabilities to safely and effectively perform the activities necessary to undertake the learning activities and achieve the learning outcomes of an award.

Cognitionkeyboard_arrow_down

The inherent requirement for cognition is possessing the intellectual, conceptual, integrative and quantitative capabilities to undertake the learning activities and achieve the learning outcomes of an award.

Communicationkeyboard_arrow_down

The inherent requirement for communication is the capacity to communicate information, thoughts and ideas through a variety of mediums and with a range of audiences.

Behaviouralkeyboard_arrow_down

The behavioural inherent requirement is the capacity to sustain appropriate behaviour over the duration of units of study to engage in activities necessary to undertake the learning activities and achieve the learning outcomes of an award.

Learning outcomes

1. Demonstrate broad and coherent knowledge in core aspects of Information Technology, including programming, data storage and modelling, cyber security, networking and statistics.
2. Extract usable information from a variety of structured and unstructured data sources.
3. Work effectively as a productive team member on an industry-relevant project.
4. Apply advanced machine learning and data mining techniques for analysing both small and large quantities of data.
5. Develop specialised data management strategies pertinent to big data technologies on and off the cloud.
6. Formulate and proficiently apply advanced statistical modelling techniques, including generalized linear models and models for multivariate analysis.
7. Identify, select and evaluate pertinent statistical methods for data from a broad range of statistical applications.
8. Assess the theoretical assumptions of machine learning and data mining methods in relation to a variety of practical applications.
9. Independently integrate research and a variety of specialised analysis techniques such as statistical modelling, machine learning and data mining, and exploit them to solve complex real world problems.
10. Describe and explain the social, ethical and legal issues relevant to machine learning, data mining, and big data technologies.
11. Effectively use techniques for communicating complex ideas and results to a wide range of specialist and non-specialist audiences in multiple modes, including verbally and in writing.

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