Why study data science online: A student Q&A

Find out what it's like to study data science with Southampton Data Science Academy with our student interview. 

John Tricker is a recent graduate of Southampton Data Science Academy’s six-week online Fundamentals of Data Science (Non-Technical) course. We spoke to John about what motivated him to upskill in data science, how he fit studying in alongside his full-time job, and the support he received as an online student.John Tricker

What motivated you to study data science online with Southampton?

John: For the past 12 years I've mainly been focussed on learning and development roles, which means I have been working in different organisations on performance and training. I’ve not studied data science before, so this was an entirely new field for me.

Like everybody now, I’ve become saturated in data, with so much information that I need to use every day. I've always been in meetings and had communication with people at work that seemed to be wizards with the data that I seem to get lost in. I wanted to do a course that would allow me to start interpreting that data, help me make better decisions within my role and to help others to do that too. I knew there was going to be support from tutors as well if I chose to study with Southampton.

How many hours did you spend studying a week?

John: Across the six weeks I would say it varied week to week. It was important to me that I was able to manage the time. Not only am I working full time, but my daughter was born almost a year ago. That keeps me busy. The advice is around six to 10 hours a week.

In the weeks with assignments, I spent a little bit more time studying, as I really enjoyed the assignments. It’s like anything you study, if you really enjoy it and put in a lot more, then you get more out of it. There was one week when I really struggled with managing the course and home life. And I spent a lot less time studying in that week, but that was fine because of the way the course was set up. I could catch up in the next week.

What level of support did you receive from academics?

John: I was so surprised by the amount of support that I received on this short six-week course. The responses to my questions came within 24 hours for every question that I sent via email. There were two live sessions a week. There was the group tutorial with all my classmates, which was led by the tutor. It was a wonderful group to work with, share what we're learning and support each other.

Then I had the opportunity to book a one-to-one tutorial every week. This was great because I felt I could talk about the things I was most curious about in that tutorial. The tutor sent me loads of other resources, blogs and coding sites to look at as well. It surpassed my expectations in terms of tutor support. My tutor has invited me to lots of other events and webinars that she's doing now, so the support has continued after the course.

How can you apply what you’re learning in your day-to-day role?

John: Within six weeks, I developed real skills from the course. How to clean and sort data, how to create a schema and then the data analysis and visualisation are all skills that I’m proud to add to my CV.

We used Tableau and a few other platforms to create data visualisations, which allowed storytelling to be done, telling an impactful and emotive story around what the data really meant. That was probably the most enjoyable part for me. It's transformed my ability to do that within my work, which I didn't expect from the six weeks of the course.

How is your work assessed and can you talk to us about your assignments?

John: One assignment was focussed on information from a Tanzanian health care facility. It was messy data in different tabs, all the formatting was off, and some data was mixed up. In the beginning, I was confused, and I had no idea where to start. However, the resources in the tutorials helped me to work out how to create the schema for the data, how to sort it, how to clean it, and then how to organise it in a way that would be ready for analysis. The assignment was to clean and present the data, but then also provide a report of the process of doing that.

The grading rubric was clear from the beginning, so I knew what I was being graded and going to get feedback on. It meant that I could create my assignment around what I knew the feedback was going to be focussed on, which was useful.

Are there any current trends or topics in the field of data science that the course can help you gain a better understanding of?

John: One thing that surprised me was the big picture thinking from the course, around data ethics. The moral question about open data is who should be able to access it? And do citizens have the data literacy skills to be able to understand the data, and to know who is using it? Should organisations and schools and universities make aspects of data literacy something they teach?

In the future everybody is going to be using data to a certain extent. The big moral questions around open data and data literacy, and whether governments and organisations and schools are doing what they need to do to prepare people for the future of data was fascinating.

Thank you to John for sharing his insights into the course!

Southampton Data Science Academy's online courses are tutor-led and can be studied from wherever you are in the world. Find out more:

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