"The MSc Data Science (on-campus programme) lead by Dr Daniel Stamate is the right balance between theory and practice, across all modules I studied. The strong point of the MSc Data Science is that students can choose the subject for their coursework, for example, finance, medical studies, transport, etc. as long as expectations set with each lecturer are met. This enables each student to directly apply the Data Science/AI/Big Data skills to real-world problems of their interests.
It then gives the opportunity for students to build their portfolio of use cases, that can then be demonstrated during interviews.
Dr Daniel Stamate also provides the opportunity for proactive students to benefit from the ‘Data Science and Soft Computing Lab’ where students can further their knowledge, practice with real data and potentially meet with professionals from the industry. This was certainly the case in my experience and I am still in contact with some of these people to date.
I worked on many projects ranging from NLP, AI and Machine Learning domains. My major project was my MSc thesis which focused on analysing the predicting power of sentiment on the XLE index and XLE index’s constituents market trend and volatility.
On the big data side, I wrote a functional and performance comparison between two Hadoop components, namely Hive and Spark, in the context of analysing airport flights’ delays/cancellations.
On the AI side, I implemented and compared the performance of two informed search algorithms, namely the AStar and Jump First Point, based on numerous scenarios involving an agent moving in a 2D grid, containing ‘road blocks’.
I am now a Data Scientist working for a major commercial bank. As a summary, the high quality of tuition and care for students coupled with extracurricular activities proposed by Dr Stamate, as part of the MSc Data Science, have significantly helped my success in securing my ‘dream job’."