Unlocking Tech Success: Edward’s Journey from IT Expertise to Data Science Mastery

Edward has always had a natural inclination towards technology, which led him to pursue a career in the field. Being a tech enthusiast, he gained a diverse range of experience by working in various tech-related jobs before transitioning into data science.

To further enhance his knowledge and skills in the field, Edward completed the Data Science & AI program with the Institute of Data. The program helped him solidify his understanding of the tech industry and introduced him to new concepts that he has implemented in his current role.

Edward’s passion for technology and data science has been instrumental in his career progression. He is currently thriving in his latest role, and his expertise in the field continues to grow. We caught up with Edward to learn more about his journey and how the Data Science & AI program has helped him achieve his career goals.

1. Can you please tell me about your professional background and the journey that led you into the tech industry?

I moved to Melbourne about twelve years ago. I love it here as there are so many interesting people and opportunities, and something is always happening.

I finished high school on a Friday and started working at an IT company the following Monday!

I’ve worked as a computer technician, printer repairer, and Apple technician. I was also the assistant manager of a computer store, as well as a workshop manager at Higher Intelligence and then a service delivery manager at Green Technology Management.

I wasn’t really happy with my career progress or direction, so I decided to attend the Royal Melbourne Institute of Technology (RMIT), where I completed a degree in Information Technology (IT). I’ve since completed a post-grad in data analytics and, most recently, the Data Science & AI program at the Institute of Data.

2. What made you decide to study with the Institute of Data?

I was looking at master’s programs, but they seemed crazy expensive. So, I started looking into alternatives. I was also quite keen to study online.

After searching online, I found the Data Science & AI program at the Institute of Data and thought the course material and the program’s direction all looked really interesting.

I liked the pricing and the way the program covered many areas quickly, and it introduced a range of topics in an ordered and constructive way.

I found the communication and expectations clear, and I liked the flexibility that the program offered.

3. How did you find the program overall?

I quite enjoyed it. I was lucky that I’d recently completed my IT degree. I found some programming aspects challenging, but my pre-existing knowledge base proved helpful throughout.

As far as highlights go, learning about principal component analysis (PCA) was mind-blowing.  To me, it is akin to the double-slit experiment in physics – it’s like wizardry!

4. The program has lots of extra resources on offer. Did you find them useful?

There were a huge number of ebooks and other resources that were shared with us. But what was really good was having a tutor available to call on if you needed help.

5. Can you share the techniques or methods you employed to complete the course successfully?

I was working full-time throughout the program.

Regarding techniques, I tend to write everything down during class. This process pushes the knowledge through my head, hand, and onto paper. Writing things down physically helps me remember them. That then supports understanding of the concept.

6. Tell us about your capstone project.

I have been surrounded by medical professionals for most of my life. My father was an anesthetist, a large number of my friends are medical professionals, and my partner is a speech pathologist. It felt natural for me to choose a project in the medical field.

I decided to challenge myself and build a neural network to perform diabetic retinography to predict whether a patient had diabetes.  There were significant challenges in processing the images, issues with computer resource limitations (memory and processor), and trying to tune the network itself.

I had loads of support from the tutor, helping me to try and find the issues with the model and why we weren’t getting the output we wanted.  Ultimately it proved unsuccessful, but I learned a lot along the way.

After finding that it wouldn’t provide me with something I was happy to present, with only 24 hours remaining before the submission deadline, I started from scratch again.

I trained a new, high-accuracy model based on a numerical dataset instead, wrote the report and completed it with only a few minutes to spare before presenting it!  It was a glowing success, even if it wasn’t what I had originally intended.

7. Has the Institute of Data prepared you to work in the industry?

Through the Institute of Data’s program, I learned how to use new platforms, such as Jupyter Notebooks, which will be very useful in my new role as a business intelligence analyst.

The new platform that my company is implementing uses Jupyter Notebooks at its core for customising its predictive modules, so it is fantastic that I have experience with them.

It was great to be able to become more familiar with predictive analytics, machine learning and neural networks, as they will be very useful for me over the next few years.

8. Have you been able to apply the skills you learned at the Institute of Data to your career in data science?

Yes. I now work full-time as a Business Intelligence Data Analyst for Buller Ski Lifts (BSL). I get to work between the city and the snowfields. It’s an absolute dream come true.

9. What do you love the most about working in the data science & AI industry?

The tech industry is exciting, especially in the data science field, because everything is progressing so dizzyingly fast.

That keeps things exciting and interesting. I love learning and knowledge sharing as they are a few of my values, so it is a great career to be in, as there is a huge need to discover insights and then communicate them to a range of audiences, both technical and non-technical.

10. What advice would you give to someone that is interested in joining the tech industry?

Networking, tuning your resume, learning how to write a really good cover letter and most importantly, how to interview well.

There are some who believe that a cover letter isn’t needed these days, but mine was the primary reason I got the interview with BSL. I would have been overlooked if I hadn’t talked about why I wanted the job and my passion for the industry.

Interviewing is also a skill that you need to learn. Knowing how to correctly answer the questions in ways that communicate more than just the information they asked for will get you a long way.

It doesn’t matter if you make mistakes or aren’t successful at first; that’s all part of learning.

The important thing is to keep trying and learning. Along the way, you’ll gain knowledge and experience you can leverage.

Just keep pushing, and you’ll get there – don’t ever give up. At times, I felt like I wasn’t going to be successful, but that’s when you just have to have faith in yourself and keep going.  Keep learning and applying for the job you want.

Conclusion

If you want to pursue a career in tech, or more particularly, data science & AI, schedule a consultation with one of our experts at the Institute of Data to kickstart your journey with a concrete plan.

You can connect with Edward and follow his professional journey on LinkedIn.