My First 13 Weeks :

1. Before Rockborne

I would like to set out a picture of who I was before Rockborne. I have just finished my exams in my final year of university in which I studied Electrical & Electronic Engineering, and soon to be a graduate. After my exams, I knew straight away which career or job role I wanted: a Data scientist.

As an engineer, how did I come across this career option?

It started at university while I was working on my final year dissertation, where I had to run machine learning models on a dataset. This led me to learn the data science process:

• Data Gathering
• Data Cleaning
• Data Exploration
• Modelling
• Interpret the Results

I fell in love with this process, it was something that I really enjoyed doing, getting insights from data, making models and then explaining my results. This pushed me to apply for jobs in data science, however LinkedIn and other job posts showed me the unfortunate reality. Most jobs posts although specifically say “Entry Level” required 2+ years experience in the data industry with certain technical skills, which were in summary:

• 1 or 2 programming languages (Python, R, C++, Java)
• SQL
• Data Visualisation Tools (PowerBI, Tableau, Excel)
• Machine Learning

You can already imagine, I only had a few of these skills which made me think that maybe I am not suitable to become a data scientist, soon after I came across a job post about a graduate scheme, where the company will train me for 16 weeks on different areas of data roles and then be sent off to one of their clients to work there as a consultant. The name of that company was Rockborne.

2. During Rockborne

The training at Rockborne was fantastic, it was full of contents and with loads of materials, in addition, I was getting paid during this period, which was a great selling point for me, because it kept my motivation high. The environment felt similar to university without the stress of exams.

These are the things that I have learned:

• Excel
• Python
• SQL
• Tableau
• PowerBI
• Machine Learning
• DevOps
• Presenting

All areas that I needed to have a good understanding if I wanted to become a data scientist in the future. Not only they trained me, but also gave me projects to do and present my findings to stakeholders, just like what I would do during my placement. My brain during this period was in full “sponge” mode, I was absorbing information like never before, I was excited to learn and to put in practice my newfound knowledge. I gained valuable feedback both from the data coaches and my cohort, it helped me to improve my presentations, communications and my team building skills.

My favourite part throughout this was the people, everyone was helping each other to give out their best in both technical and non-technical skills. The data coaches were amazing, if I were to get stuck in a problem, they were able to stare me in the right direction to solve it, as I enjoy solving puzzles. As a gamer, there is nothing more liberating than defeating a tough boss, and this is how I felt every time I found a solution. In conclusion, I have learned valuables skills that will be stuck with me forever and I developed an always-learning culture.

3. What is Next?

I am currently working towards my cloud certification, getting prepared for interviews and doing personal projects on the side, to polish my skills and try to experiment with new machine learning models. For example, I am learning generative adversarial networks (GANs), which is one of the building blocks for AI-generated art.

Find out more about the Rockborne graduate programme here.