My First Semester as a Part-Time Student in an Online Data Science Masters
Going back to university as a mature student can be intimidating, but pursuing a master’s degree has been a goal of mine for a while. I finally decided to take the plunge and applied to a well-regarded Data Science program at The University of London Goldsmiths. Here’s a breakdown of my experience with applying, registering, enrolling, and studying during my first semester.
Applying
The application process was straightforward. I was required to provide a brief personal statement and two academic or professional references. I asked my line manager and a coworker who I had worked on several projects with, and both were happy to provide references. The application fee was £100, which I thought was a little high, but I took it as a loss.
The decision reached me relatively quickly, and I received an email telling me I was accepted. I accepted the offer and was excited to begin my studies.
Registering
After accepting my offer, I was told that I needed to complete a prerequisite course on Coursera. I did this and got the certificate, but registering for the program ended up being a bureaucratic nightmare. I didn’t receive any confirmation, and the module enrollment deadline was approaching quickly. I had to make a lot of calls to student services, who seemed overwhelmed, and finally had to escalate my complaint until I reached someone who could help. I almost gave up, but later found out some students hadn’t received their registration confirmation until midway through the semester. Not the best first impression!
Eventually, I was able to register and enroll in the modules I wanted to study.
Enrolling
I had to enroll in each module I wanted to study and pay for them before I could start. Not every module is offered every semester, and some are required. I chose two intro-level modules that were being offered: Statistics and Statistical Data Mining & Data Programming for Python. I chose only two because I did not want to overload myself, but I could have taken more or less. Once I paid, I had access to the course materials in the Virtual Learning Environment.
The total cost for my first semester was £2,236, which I paid on my credit card and then paid off when I received my Student Loan payment.
Learning Structure
Each class/module was divided into ten topics, which are each meant to be studied over two weeks. We have a 22-week semester in total, with the last two weeks left for revision. The lectures are pre-recorded, and there are additional materials like suggested readings, exercises, and forums where you can chat with other students. There are seminars, but they are module-specific. One had them every fortnight, and the other had only two for the whole semester, at the beginning and end.
Exams and Coursework
These are set at the module level. Statistics had a coursework due in December, which I found quite easy and received a good score for, and an exam in March, which was a bit more challenging. The coursework provided a skeleton Jupyter Notebook and asked us to complete a series of manipulations on the data. They were each 50% of our final mark.
Data Programming had two coursework assignments and no exam. The first was an Exploratory Data Analysis of a dataset of our choosing, which made up 30% of the mark, and the second was a full Data Science project of our choosing on that data, making up 70% of the final mark.
Interacting with Staff and Other Students
I found it quite frustrating that the only way to contact staff, including tutors and lecturers, was through the online portal. We were not allowed their email addresses, and they did not have virtual office hours. There were student WhatsApp groups for each module, and other students were very helpful and supportive. I did wish the staff would have also joined these.
We’ve been told there may be an in-person event organized in the summer, but no dates have been given yet.
How I Studied
As for how I studied, the Statistics course required a lot more study and revision as it was an unfamiliar topic. I watched every lecture and took notes, and then reviewed and compiled those notes based on the provided outlines. The Data Programming course was poorly structured, so I abandoned the lectures and stuck to reading the textbook. It also helped that I was familiar with the topic already, and only took this module as it is required to complete the course. I focused most of my time working on the coursework and learned a lot from that.
My study time varied a lot due to illness, work, and just life in general. Some weeks, I was able to study for 20 hours, while other weeks, I only had 5 hours available.
Final Thoughts
In conclusion, I learned a lot, but I would say it was mostly self-study with Data Programming, whereas Statistics was around 70/30 taught vs self-study. Even with the self-study, having a deadline and a goal to work towards helped keep me focussed, which was exactly why I wanted to pursue a Masters in the first place.
I’m pleased with my performance this semester and cautiously optimistic about the summer term. I plan to only take one module unless there are two I really want to take since I have a lot planned for the summer already. Despite any frustrations with the course or the university, I am still glad I decided to study this course and I feel it was worth the time and money I’ve invested so far. The next semester starts in April, so I will continue to update here as my studies progress!
