Case study: Upskilling in Data Science with an MSc degree apprenticeship

Delivered by Cambridge Spark, Anglia Ruskin University’s MSc Digital and Technology Solutions (Data Analytics) degree apprenticeship equips learners with the tools and techniques to process large complex datasets for business insight.

Dr Sylwia Macinska, Senior Research Manager at Cambridge Assessment, started the two-year apprenticeship in September 2019.

Sylwia first developed an interest in data analysis and modelling whilst studying for her Psychology PhD, and her current role at Cambridge Assessment is heavily focused on using data analysis to find innovative solutions to support learning. With a desire to find more effective ways to analyse data and to model the behaviour of students to predict performance, she applied for the MSc apprenticeship after seeing it advertised by the organisation she works for, Cambridge Assessment.

“I thought this was a very exciting time to upskill in data science so we can create more innovative solutions to support teaching and learning. We have been carrying out research, tracking student progress, and analysing data to improve learning for a long time. But now with new opportunities offered by digital data and computational techniques from data science, we can create a more comprehensive picture of learners and provide them with a more personalised experience based on their strengths and areas for improvement”.

Dr Sylwia Macinska, Senior Research Manager at Cambridge Assessment

Learning practical skills

Sylwia dedicates one day a week to the apprenticeship but is able to apply those skills to the rest of her work.

“I have been able to apply my new skills to a variety of projects. For example, in one project we wanted to evaluate student engagement and see whether we could predict students that may need targeted support. That has been very promising so far.”

Dr Sylwia Macinska, Senior Research Manager at Cambridge Assessment

The apprenticeship has equipped Sylwia with a comprehensive set of data science skills, including machine learning techniques, data engineering and deep learning;

“The apprenticeship has taught me all the skills and tools to get into the flow of data science. Each of the modules has contributed in some way. The knowledge gained from the data engineering module means I no longer have to rely on someone else to provide me with data in Excel format. I can now access the database directly and simply extract the required data. The exploratory data analysis module improved my ability to perform initial investigations on data to discover patterns or spot anomalies. I have learned various strategies for feature selection. Then once I was able to prepare the data for modelling, I could apply and evaluate performance of the different machine learning techniques we were taught.”

Dr Sylwia Macinska, Senior Research Manager at Cambridge Assessment

Immersive learning and expert teachers

The course is taught via a blend of immersive teaching, online study and a hackathon-style bootcamp which simulates real-world events. Sylwia particularly enjoyed the practical exercises which she believes helped to accelerate her learning.

“The course was very hands-on with lots of practical exercises, which is great because I always learn better by doing things rather than through observation. For example, when studying machine learning techniques module, there was a Jupyter Notebook available with a variety of examples of how to apply each technique and in what context. Being able to work through those examples myself from start to finish showed me how I could apply them to my data.”

Dr Sylwia Macinska, Senior Research Manager at Cambridge Assessment

On the teachers and the structure of the apprenticeship, Sylwia says, “The teachers were very excited about the subjects, and it’s always helpful to see this enthusiasm and passion coming from people that share the knowledge with you. The live sessions were interactive and we were able to ask questions and go over concepts if we needed. I found EDUKATE.AI useful too, in terms of being able to get immediate feedback on your code.”

Career progression while learning

Halfway through the apprenticeship, Sylwia moved into her new position of Senior Research Manager and believes her training was a contributing factor to her being successful in getting the position. She says, “I think that I am perceived as someone who can be a bridge between the researchers and data scientists that are currently working in the organisation, to help bring together the two worlds.”

Sylwia is now heading into her final project and is looking forward to bringing together everything she’s learned throughout the course. Sylwia joined the apprenticeship along with eight others from her organisation and believes even more people could benefit from data science skills.

“Everything is data-driven these days,” she says, “There are so many positions that you wouldn’t think would be related to data but could benefit from learning about data science and how it can be applied in their organisation”

Dr Sylwia Macinska, Senior Research Manager at Cambridge Assessment

You can find more information about the MSc Digital and Technology Solutions (Data Analytics) Apprenticeship here. Or if you want to speak to someone at Cambridge Spark about the apprenticeship, please get in touch.

Apprenticeships provide a well-defined route for upskilling people in data analytics, data science and AI. Cambridge Spark offers a number of learning pathways, for people working in data-related roles wanting to find more efficient ways of doing things all the way through to software engineers wanting to advance their skill set. Find out more here.