Bachelor of Engineering (Honours) Data Science Engineering

Diploma in Professional Engineering Practice

Data science engineers manage the collection, storage, transformation and delivery of data with the quality, security and reliability required by modern organisations to succeed in today’s data-driven world. This major builds your skills in data science, data analytics and machine learning as well as cloud computing, cybersecurity, big data management and software engineering for building and maintaining data-driven systems.

In the Data Science Engineering major you will learn the theoretical foundations, entrepreneurial values and professional skills required to build and manage data platforms of all sizes. You will develop skills in research and advanced practice, gain in-depth knowledge in one or more areas of specialisation, and learn to embrace innovation in order to achieve excellence in engineering.

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Course overview

The skill-set of a data science engineer, or data engineer for short, is one of the broadest in the industry, encompassing data warehousing, 'extract-transform-load' (ETL) tools, distributed systems, and machine learning. Data science engineers play pivotal roles in key sectors including finance, healthcare, e-commerce, transport, defence and media companies.

The Data Science Engineering major includes a series of studio subjects where you apply your learning to address challenges typical of large, complex and critical data-driven systems. Alongside the project work, the studios invite you to undertake self-directed learning on topics of personal or professional interest and to tailor your skills to your future career. The studios also include opportunities to engage with industry-led projects, cutting-edge research, and entrepreneurial activity, and are a great way to build your professional portfolio.

The Data Science Engineering program is divided into three key stages:

The Fundamentals Stage will give you core skills in the sciences, as well as in the foundations of data science engineering. This stage includes two semesters of practical studios that extend and embed what you have learned in class, as well as the chance to pursue elective subjects from any UTS faculty.

In the Applications Stage you will undertake intensive study in the data science engineering specialty of your choice. The studios in this stage are designed to enhance your theoretical knowledge and increase your engineering capabilities through interaction with University and industry experts.

The Honours Stage includes a year-long Honours Project. You can choose to conduct leading-edge research or undertake an innovative project that could lead to start-up opportunities.

In parallel with your progress through these three stages, you’ll also undertake a professional development stream that builds your capabilities in areas such as entrepreneurship and project management. This stream it has its own learning outcomes, and includes two semesters of studios that will connect you with industry mentors and emphasise innovation and readiness for professional practice. 

Transcript

0:02

Engineers are the people who make a difference to this world, and data engineers are the

0:07

people who make a difference to this data-centric world, and this data-centric world is really

0:12

very exciting.

0:13

It’s all about what we do with data, how we manipulate data, how we use it to improve

0:18

our lives, how we use it to improve the world.

0:21

So that’s why it’s a fantastically exciting field to be in.

0:25

So it’s four academic years, but we split those academic years into five, into four

0:35

stages.

0:36

So there’s a fundamental stage, so during the fundamental stage, students are learning

0:40

about the scientific and professional bases of the profession of data engineering, and

0:46

then there’s an applications phase, or applications stage, and it’s during that stage that students

0:53

do a specialisation in a particular area of data engineering.

0:57

And across all of these is something we call the professional sequence, and these are professional

1:03

activities that students do in order to become rounded professional engineers, and also to

1:09

meet the requirements of Engineers Australia, which are very important.

1:12

And finally the whole thing is capped off by an honours project, and this is an opportunity

1:18

for students to do a high quality research project, or perhaps become innovative and

1:24

create a start-up industry, or perhaps do some kind of professional activity with an

1:31

outside partner.

1:32

So those are the stages of the degree.

1:35

UTS Engineering has a very interesting feature – it’s the Diploma of Professional Engineering

1:41

Practice.

1:42

It’s well known throughout Australia and throughout the world as being an outstanding

1:49

part of the degree program.

1:50

It’s two periods of time in which students do internships in industry, but these aren’t

1:56

just internships just going off and doing something in industry.

2:00

These are programmed parts of the actual degree itself.

2:04

At the end of this degree, not only will students know how to enter the profession of data engineering,

2:09

but they’ll be able to create their own jobs – they’ll be able to create their

2:13

own industries.

2:16

A very big part of the degree program is entrepreneurship, and the creation of start-up companies, and

2:21

at UTS is a very strong culture of trying to help students, and enable students, to

2:28

become entrepreneurial and create their own businesses.

2:31

The other side of the whole thing is we’re not only training engineers for Australia

2:35

– this is a global degree.

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This is used all over the world.

2:41

So it’s not only Australia that you’ll be finding work, it’s all over the world.

2:46

I don’t know if any data engineer is out of work – I don’t think it exists, a data

2:51

engineer who’s not in a job.

2:56

Opal collects information from the use of the Opal card against readers.

3:02

It then transports that information to a series of stand-between servers, stores it there

3:08

for a while and ultimately forwards it to a back-end system to process.

3:12

That processing lets us do two things: one is to charge the correct fare, which is, for

3:17

a fare collection system, really important.

3:19

But it also means that we can take that information and we can aggregate it, and we can use it

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for purposes such as planning of public transport services or looking to see if public transport

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services are hitting the mark from a customer perspective in terms of patronage.

3:33

There really won’t be enough data engineers out there, so I think the opportunities are

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going to be fairly limitless, the idea of being able to deal with data as a whole is

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going to be extremely important I think going forward.

3:50

goes on, so I think there’ll be vast opportunities for those who come out with that degree.