Introduction

With every click, swipe, search, share and stream data is created. The rate of data generation is phenomenal and its volume and complexity gives rise to considerable opportunities as businesses strive to harness the power of big data to remain competitive. Throughout this course you will explore the entire lifecycle of data to develop a deep understanding of how information is created, gathered, processed, analysed and used to generate insights and inform strategic decisions.

Deakin University, Australia  

Located in Victoria, Australia, Deakin University is a public university. The university was named for Australia’s second prime minister, Alfred Deakin, when it was founded in 1974. Along with the online Cloud Campus, its main campuses are in the Burwood suburb of Melbourne, Geelong Waurn Ponds, Geelong Waterfront, and Warrnambool. ERCI runs its classes on a lecture-tutorial system. The average teacher-student ratio for lectures and tutorials are as follows:

• Lectures – 100 Students to 1 Lecturer
• Tutorials – 35 Students to 1 Tutor

Course Delivery

This programme is available in full time mode, and will take 36 months to complete. Students will attend 9 semesters of academic study, and are expected to complete up to 4 credit points each semester. Students will attend classes 5 days a week on weekdays.

Course Structure: Bachelor of Data Science

Module Descriptions

Year 1

• Academic Integrity Module

Students will develop knowledge, skills and good practice principles to understand the importance of maintaining academic integrity in their studies and career and to avoid breaching academic integrity standards.

• Safety Induction Program

This is a program of safety information for students involved in information technology laboratory work. The program encompasses information technology hazards, building evacuation procedures, laboratory accident management, first aid procedures, and safety procedures particular to laboratory work.

• Career Tools for Employability

Emphasizing the creation of a strong online presence, including crafting effective resumes and LinkedIn summaries, students develop vital communication skills for professional advancement

• Computer Systems

In this unit, students will learn the building blocks of computing systems and the tools used information technology professionals. The unit connects students with hardware and software elements of computer systems, ensuring they are ready to engage with configuring, operating, and building computing systems.

• Discrete Mathematics

Students will learn how to rigorously build, from first principles, the tools needed to address a wide range of mathematical and scientific problems. The topics covered include number theory, propositional and predicate logic, graph theory, sets, functions, recurrences, and combinatorics.

• Introduction to Data Science and Artificial Intelligence

 Students will develop knowledge of fundamentals in data science, in particular data manipulation and algorithms for analytics. Students will be able to obtain data, recognise data formats, summarise and visualise relationships in the data, perform exploratory data analysis tasks and build predictive models.

• Introduction to Programming

 In this unit students will learn the fundamentals of structured programming and explore the mechanics of how these programs operate within the computer.

• Database Fundamentals

Students will learn how to construct entity-relationship (ER) diagrams, ensuring that the model’s semantics match those of the real-world object it represents. It also teaches how to construct, maintain, and retrieve information relational databases using SQL. Through real-world business case scenarios and project-based learning, students will gain the skills required to design, implement, and manage databases.

• Introduction to Statistics and Data Analysis

Students will develop knowledge of the fundamentals of probability for reasoning real-world situations. Students will be required to use statistical software and calculators to analyse data and interpret results for tests on population means and proportions, chi- square tests, correlation and linear regression, and one-way ANOVA.

• Object-Oriented Development

 Students are introduced to object-oriented programming as the fundamental paradigm of modern programming languages and software development. Upon completion of the unit, the students will be ready to develop real-world software following the software design and structure best practices.

• Linear Algebra for Data Analysis

 This unit introduces students to vector spaces, matrix theory, systems of linear equations and methods for solving them, eigenvalues and eigenvectors, and their application to similarity of diagonal matrices. The techniques that students learn from this unit will enable them with the analysis of complex data and ensuring its reliability in studies of cryptography.

Year 2

• Computer Networks and Communication

Students will gain a deep understanding they need of how network protocols across the stack operate, while providing them with the programming and technical skills needed to analyse them. This will provide the focused technical foundation they need to be successful in the course.

• Data Wrangling

Data wrangling is the process of preparing the raw data appropriately for modelling purposes. The aim of this unit is to learn various data wrangling methodologies and programming techniques to perform them.

• Data Structures and Algorithms

This unit introduces students to in memory data modelling and computational trade-offs when developing software. This unit will extend student programming capabilities by exploring the application and implementation of different data structures and algorithms and considerations associated with appropriate selection of these tools to meet different system requirements.

• Introduction to Responsive Web Apps OR Cloud Computing

Introduction to Responsive Web Apps
Students will learn basic networking protocols and fundamentals for web, HTML, CSS and advanced web design frameworks such as Vue to build web apps both for desktop and mobile devices. Students will develop an understanding of how web infrastructure, design and programming work together, as well as learn fundamentals of responsive and progressive web design and deployment.

OR

Cloud Computing
Upon completion of the unit students will have a clear understanding of cloud computing, the technologies used in provisioning clouds, the application of cloud computing to solve problems, and the issues that must be considered when deploying cloud technologies in an organisation.

• Professional Practice in Information Technology

Students will be introduced to IT workflows, agile project management, dev-ops pipelines, version control, and the ways these tools fit together in modern companies. The use of these technologies is underpinned by the behaviours, teamwork, and ethical considerations needed to engage in working in IT in a professional manner.

• Feature Generation and Engineering

 This unit will equip students with the knowledge and skills to identify and generate features from different raw data inputs (text, image, video etc.) or signals (accelerometer, electrocardiogram, financial time series) to build machine learning models.

• Data Capture Technologies

 Students will be introduced to a range of data capture protocols and methodologies. Students will use industry-standard approaches for data presentation, visualisation and analysis.

• Full Stack Development: Secure Backend Services OR Cloud Automation Technologies

Full Stack Development: Secure Backend Services
This unit focuses on the backend technologies for the full stack development, including programming service APIs, creating databases and cloud deployment.

OR

Cloud Automation Technologies
In this unit we will examine how to package modern network services and then deploy them to the cloud using Kubernetes. Students will learn what containers are, how they are created, and how they are used in software deployments. 

Year 3

• Natural Language Processing

 This unit provides students with a deep understanding of the basic theories and techniques used to process large-scale of text document data to understand, search, identify, and extract information from semi- structured text documents. The unit will cover basic technologies for text document analysis, including information retrieval, search and indexing, information extraction, document classification, and natural language understanding.

• Machine Learning

Students will explore machine-learning techniques such as data representation, unsupervised learning (clustering and factor analysis) methods, supervised learning (linear and non-linear classification) methods, concepts of suitable model complexity for the problem and data at hand

• Full Stack Development: Secure Frontend Applications OR Cloud Native Application Development

Full Stack Development: Secure Frontend
Applications
This unit focuses on the frontend part of the full stack development process by using web technologies for programming frontend interfaces, interact with services and databases to create applications that support a wide variety of device capabilities.

OR

Cloud Native Application Development
In this unit students will learn to design, develop, and deploy of cloud native applications according to best practices including infrastructure as code, asynchronous communication, instrumentation, latency management, replication and parallelization, failure management and security.

• Team Project (A) – Project Management and Practices

 Students will learn about project management methodologies and practices, with a particular emphasis on agile project management. Students will develop hands-on experience in using industry- standard tools to contribute to the project, analyse requirements, design solutions, monitor project progress and productivity, and reflect on sprint and project outcomes.

• Deep Learning

This unit is for students to develop practical knowledge of deep learning and associated applications. Learning activities will focus on understanding deep learning theories, constructing deep learning models for handling structured and unstructured data, such as images, videos, and texts

• Mobile Application Development OR Software Architecture and Scalability for Internet-Of-Things

Mobile Application Development
Students will cover the design and the workflow of developing apps in one mobile application platform, a framework for constructing an application, as well as tools for developing, testing, and publishing software for the platform. Students will focus particularly on learning advanced concepts and APIs, and putting those skills into practice to develop a real-world mobile app.

OR

Software Architecture and Scalability for Internet-Of-Things
Students will learn and use different architecture patterns including layered architectures, message-bus style, event-driven, micro services. Students will also learn different deployment models, quality of service attributes and trade-offs and testing requirements and frameworks.

• Team Project (B) – Execution and Delivery

Students will identify a potential problem or technical gap and experience how to solve it using methods, algorithms and techniques pertinent to the field of IT. Students will be required to further formulate necessary design and/or development strategies, work collaboratively with peers to manage and conduct the implementation of the project and demonstrate outcomes achieved against project goals and targets.

• IT Placements and Industry Experience 

In this unit, students will undertake professional work experience with an approved host organisation for a minimum of 100 hours. This systematic opportunity will provide students with experiences being in an organisation, critically reflecting on their Course and Graduate Learning Outcomes, and their discipline- Course Details specific and generic competencies

Course Availability

Intakes for the programme are available 2 times a year. All applications should be submitted to ERCI no later than 2 months before the commencement date.

Assessment Framework

Courses are assessed by a combination of coursework, practical assignments and examinations. Formative assessments will also be included, as well as self- and peer-assessment and a capstone project.

Entry Requirements

Academic:

• Minimum 3 GCE ‘A’ Level passes (with Grade D and above) in Mathematics and 2 other subjects other than English Language OR
• IB Diploma OR
• 12 years of formal education from recognised international institutions OR
• Any combination of the above or equivalent as determined by the university as successfully meeting the minimum entry criteria of 12 years of formal education

Note: for mature students who do not meet the above entry requirements, they must be 30 years and above with a minimum of 8 years of working experience and meet language requirements.

Language:

• Grade C in the General Paper or in a Humanities and Social Sciences subject at H1 or H2 level at GCE ‘A’ Levels OR
• IELTS overall score of 6.0 (with no band score less than 6.0) or equivalent

Age:

• Applicants should be at least 18 years old (based on birth year) at the time of registration

Graduation Requirements:

Students must successfully complete, or be credited with, 24 credit points within the stipulated period of study as set by the University, either via module exemptions or completion of requisite modules.

Course Fees

For a full listing of course fees and other charges, please select one of the following:

• Fees Payable for Local Applicants
• Fees Payable for International Applicants