This is the transcript for the video Data Science Engineering
Cherry Katyal 0:05
So in this session, we are going to be of course discussing, what is data science engineering you might have heard of it, you might not have, you might have heard of data analysts or scientists, but maybe not data science engineers. So we’ll get to that. We’re going to be looking at the possible careers in data science engineering, and some of the overlaps that we might face. We’re also going to be looking at the areas of engineering and UTS specific courses, how to best prepare to study engineering at UTS. So what is data science engineering? So data science engineering, it’s basically creating the infrastructure needed for data science, artificial intelligence, and machine learning, you can kind of get that just from the name itself, we focus on the technologies for collection, transmission, storage and analysis of data. So currently, I’m doing a cadetship at transport from New South Wales. I’m working with a bunch of data engineers, and then I kind of see this in action. I’ll use an example, of opal cards, I’m sure every one of you guys have either have an Opal card, have you seen the little scanners. But the technology that is used to collect that data is what data engineers focus on. We collect that raw data, we transform it, we can store it in some places and we can also use that data for analysis for business outcomes for better decision making processes. I’ll get to that later, but that’s where data scientists and engineers and analysts sorry, also come in. So the technologies we focus on can range from cloud storage, which is just a fancy way of saying internet, the computation to databases, which is something that our courses focus on a lot networking, which is another thing that we will be seeing a lot of if you choose to study data science engineering at UTS algorithms following software engineering and data science principles. It’s also one of the fastest growing professions. As we all know, we are living in the digital age. I think I saw on Sydney seek there are a bunch of job postings, and I’ll kind of talk about that later on, too. But it’s definitely something that’s in demand, if that’s what you were thinking. Now we’re looking at this hierarchy of data science, data engineering and machine learning. I just want to note that this isn’t in a hierarchy of importance. We’re not saying that data infrastructure engineers are all at the bottom, machine learning engineers up top, and we’re kind of sitting in the middle. It’s more about showing you guys foundations of what we do, and how we can build on that to achieve so much. So data engineers, we focus on not only the collection, but also the moving, the storing, the exploring and transformation of data. So data infrastructure engineers focus on the instrumentation, logging, the sensors, external data, and user generated content. So again, using the Opal example, they’re looking at the sensors that the Opal reader has. Data engineers, we are focusing on making sure we have a reliable data flow. We use, again, technology infrastructure that we built, we also build pipelines to move data from one place to another place. ETL, which is extracting transforming and loading the data. Structured and unstructured, data storage, which basically means that we kind of go through, we filter through that raw data and we kind of clean it into a way that we can actually use in the future, we take out any anomalies, any duplicates, anything like that. Then you have the machine learning aspect of it all, where there’s more of the analytics involved and the metrics. We have the segments, aggregates, features and training of the data, which is something that data scientists and analysts do. Again, I’m not saying that data engineers are not involved in that, they are, there’s a tonne of overlap in all of these careers. Then of course, we have the machine learning engineers, which look at artificial intelligence and deep learning, which is something I’m sure you guys have all heard about. It’s kind of a hot topic right now. They also use testing, experimentation and simple algorithms. It really shows that there’s a tonne of overlap here and it shows you what we actually do with data. It’s not just we’re collecting data, and we’re looking at it. We are transforming it, we’re exploring it, learning new things from it every day. We’re using data as an intangible asset now. So we’re going to talk about diverse career opportunities. So I just want to emphasise that studying data science, engineering is not limiting you to just be a data engineer. There’s a tonne of scope. There’s so much you learned from UTS that you can apply in other job opportunities, such as data analysts, data scientists, data architects, which kind of do a bit of all of that. Software developers. We do a lot of programming subjects, which shouldn’t scare you guys. We definitely get eased into it. That was kind of scary for me. I thought it would be scary, but it wasn’t at all and I’ll get to that later too. You guys can also look into big data platforms. Big data is something that is kind of another buzzword around. Of course, a data security consultant and data governance officers is just another one. There’s just a lot out there. Looking at the UTS engineering courses. As I mentioned before, I am doing a double degree. I’m studying data engineering at UTS and I’m also studying Bachelor of Business majoring in economics. We’re focusing on data science engineering today courses with the Asterix in them, they are actually using up your elective blocks. Unfortunately, they can’t be combined with other degrees. Data science, engineering at UTS. To be a data engineer, you’ll need to understand the whole data ecosystem as a whole within organisations, which is something that you definitely study at UTS. The UTS course includes core subjects on data analytics, which is data science, coding, software development, networking, and systems science. So the electives that you choose kind of are pulled from that. So your core subjects aren’t just your core subjects, they can be also implemented in your electives. So popular options chosen by students include subjects on artificial intelligence, machine learning, I have a bunch of friends doing both and they love it, I’ve heard very good things about both. Cybersecurity is also very popular and image processing. Learning is underpinned by a thread of studio subjects that span the whole degree where you get to actually apply your skills to challenging academic and industry problems, which is unique to UTS. I’ll talk more about that later. But it’s a really cool way to apply your theory to practice, which is something that is always so good, because you can only learn so much from theory, when you get to actually apply that knowledge, that’s when it actually sinks in for you. So the role of a rehabilitation engineer may include research to develop new technology, but also to make existing technology more effective fabrication of a custom Device or Device modification, testing of equipment for safety and compliance to Australian standards, and suggesting worksite modifications.
That’s also kind of related. So looking at the course structure, this is if you were just doing Bachelor of Data Science Engineering, if you were doing a double degree, it might look a little different. But this is basically it. So in your first and second year, you’ll have more focusing on your engineering core subjects such as engineering project management, and design and innovation. Those are two of my favourite subjects, you will see a lot of other engineering students from other disciplines, it’s a great way to kind of see the overlap in engineering subjects as a whole. Of course, you will have your data science engineering core subjects. Those include Introduction to Data Engineering, which is really fun, and Database Fundamentals. Of course, you you can see that we have a bunch of fundamental studios, application and professional studios. So the fundamental studios are basically you get presented with a bunch of products, and you actually get to choose a product you wish to work on and you find a team with the similar interests as you. So you spend a whole semester working with product owners and new teams to develop this product. I actually know a bunch of people that got scouted through these subjects, some of them landed interviews, some of them landed internships just from this. So it’s a great way to apply your theory in real life. If there can be industry outcomes from this too. Patients stage is where you develop deeper knowledge in your major and areas of specialisation. You might find that you want to specialise in some other area, or you want to pursue a different path in data engineering, which I mentioned, you can be data analysts or scientists, and there’s just so much scope out there. Practical experiences by studios. Studios can provide students with project opportunities to develop this as a range of professional capabilities. So you’re not only learning about the product and your specialisations, but you’re also learning about this whole professional ethic. It’s really fun having meetings with product owners and you feel like you’re working for them and you’re working for the organisation then it really puts you in the mindset of working as a data science engineer. So you have your four elective subjects too. This could be if you wish to study an exchange semester overseas, we do provide opportunities for that. If that’s something you’re interested in, that’s definitely something you should look more into. The professional stages is the hill, is basically deployment and professional experience engineering practice. So they do two six month internships, which I think I’ll talk about in a minute too. But that’s they basically do that some time between their second year and their fourth year. The honours component delivered is via in depth Research Project, which gives the students opportunities to demonstrate what they have achieved in the degree programme. So I’m doing honours, I’m looking forward to that if it’s something you do in your final year, known as your capstones, and all of our courses are focused around practice based learning, that’s something that UTS really emphasises on. It’s something that really drew me in to the university, but also the course. UTS’s Learning Futures approach enhances technology enabled and collaborative working. There’s a range of opportunities to collaborate with students in engineering from different disciplines, but also in your own discipline. That’s something UTS also focuses on is your professional and personal development as the individual, it’s not just about handing out content to you, we’re going to be looking at the Diploma in Professional Engineering Practice. So it’s basically when you complete two six month internships. It’s a great opportunity to get real industry experience before you graduate. A lot of people actually get the full time roles in their second six month internship, it’s great to have on your resume, just because it shows how much industry experience and knowledge you have accumulated over time. It’s a great way to develop your professional skills, which of course, are valued by employers, you learn a lot, and it’s also a great networking opportunity. You meet a lot of people there and it opens up a lot of doors, you will definitely find can also build networks with top organisations in the industry. Of course, UTS provides a range of opportunities to network and to find these kinds of internships, we don’t just kind of send you out there to find something on your own. We have a lot of preparation classes that help you build your resumes and your CVs. We have a lot of clubs and societies aimed at networking in a professional sense. So it’s something that we definitely focus on too. I’m going to kind of talk about myself now. So I’m doing the Bachelor of Engineering Honours majoring in Data Science Engineering and Bachelor of Business. When I tell people that I’m doing a double degree with Bachelor of Business, they’re kind of taken aback because they don’t see the overlap between engineering and business. Initially, I thought the same, I was kind of just doing bachelor of business because I genuinely love economics. And I wanted to just learn more about it. But as I was progressing, in my degree, I really realised that this a tonne, a tonne of overlap. For example, one of the classes I’m taking is econometrics and in that there’s just so much progression analysis, there’s a lot of economic data analysis. So you can see that data is not just limited to data science, data engineering, data architecture, it’s bleeding into all these other courses and all these other areas in the industry because it’s just such an in demand skill, a lot of job postings if you look through it, they’ll all ask something relating to data, data analysis, experience, engineering, it’s really something to look into. So I’m currently doing my cadetship at transport for New South Wales. I have started this year, I started playing in my third year. To be honest, it was a little tricky to find an internship just because a lot of companies don’t post data engineering internships exclusively as data engineering internships. You might find a lot of data analysis and data science internshipsbut if you look into their descriptions, it’s exactly what data engineering is. That’s how I landed my transport cadetship by going through that channel. A lot of my friends have found data engineering internships in their second year. They found that the engineering practice preparation subjects that you will be undertaking before you do your internship really prepares us well, for the internship and for the hunt for the internship more importantly. I’ve been involved in a bunch of societies. As I mentioned before, it’s a great way to meet friends, to network to learn more about yourself. I’ve been involved in the cat society, I’ve been involved in the dog society, there was a bit of tension there, but it’s always fun. I’ve been involved in the Women in Engineering and IT society, which is really fun. You’ll always see them around campus, having their events and they’re usually dressed in like businessy clothes so they look very professional. Again, it’s a great networking opportunity. I’ve also been involved in student promotional activities and peer networking activities, which is just one of the university’s initiatives to help students transition into university and learn more about the university life. There is a tonne of opportunities that you will find here at UTS for that. Another thing that some of you might be wondering is how HSC subjects, you might be wondering, what are the prerequisites for Data Science Engineering? I’m sure you’ll be glad to know that they’re none. I mean that, I was a bit hesitant to because I didn’t do any programming in my year 12 or 11 subjects. I didn’t maths but I didn’t feel too confident to pursue engineering, and that kind of threw me off. But I had actually talked to UTS about that and they did tell me that there were no prerequisites, and you are eased into everything. There’s a lot of foundational courses. There’s a lot of bridging courses, if you want to pursue, you can go for that. But it’s all very smooth, and you won’t feel like you’ve been thrown in the deep end, which is what I was scared of. It wasn’t like that at all. Yeah, as I mentioned before, why it was Bachelor of Business to do with engineering, I just loved economics and business. But there’s just so much overlap, which I wasn’t even expecting. So it’s something definitely to look into, if that’s something you’re interested in. I think that’s it for me. So I’m just gonna hand it back to Haley to continue the rest of this presentation.
Hayley Wong 15:48
Thank you, Cherry. That was great. I’m going to talk more about the overall how to get in and everything. So we’re going to talk about adjustment points for you UAC. So points can be added to a student’s raw ATAR. To give a selection rank, so pretty much you can have adjustment points, capped at 13. I know, for engineering, there is woman engineering, you can do the portfolio for edge, which I’ll talk about later and then just the subjects and stuff that you do in HSC will also matter too. So these are the key dates, which are really, really important for you guys. There’s a lot of scholarships that go on for lots of different types of things. I know there was a woman engineering one, they have one for lower socio economic schools, they have just normal ones. You just have to kind of read what the prerequisite is to get into the scholarship. Open Day is in August 27. Mark the day itself. Its our first on campus one, since two years ago, because of COVID. The scholarship applications close in September. Then the HSC is exam happen, scholarship offers get released, and then the UAC offer rounds start. So there’s going to be a few rounds, the first rounds around December I think, and then it will just keep going until end of February I think and then UTS autumn session starts in March. So UTS early entry, which was the edge programme I was talking about. So you can use your year 11 results to enter UTS. So you’re eligible if you’re a current domestic or international onshore year 12 student. You can apply through UTS online application portal, so it’s not you UAC. It’s on the UTS website and applications open around June/July. The dates haven’t been confirmed and close in September. So you get two months around to do it. Then you get provisional offers will be released on October before the HSC commences. You must complete the HSC or equivalent to be able to get this to offer. Students support. We have a lot, so bridging courses are offered if you guys ever think you have trouble with maths, physics or chem, if you guys did general maths or advanced maths, a lot of people tend to be a bit scared and then don’t think about engineering just because of that. You guys get this mathematics bridging course and it normally happens before the semester starts and it’s a crash course. So that will help in getting you to understand the next the uni maths and everything. There’s Upass too and it’s available for some subjects, mostly the bigger ones. Pretty much it’s just a student that has done really, really well in that subject. Teachers you guys were like an extra lesson and it’s free and everything. UTS provides it and it’s really really good. I learned so much for math there and everyone uses it.