Capstone (3 Credits): A semester-long group project in which teams of students propose and select project ideas, conduct and communicate their work, receive and provide feedback (in informal group discussions and formal class presentations), and deliver compelling presentations along with a web-based final deliverable. Includes relevant readings, case discussions, and real-world examples and perspectives from panel discussions with leading data science experts and industry practitioners.

Since completing my Masters in Data Science, I have had a number of people contact me asking for my experience with the course and whether it is worth recommending. Therefore, I thought it best to summarise my decision for starting the course, what I have achieved during my studies, and the outcome in the years following. It was the spring of 2016 and I was coming towards the end of a 6 month internship at one of the largest consulting firms in the City of London. I had taken this role to gain experience and figure out whether becoming an Actuary was the correct route for my career. I quickly found passion in the data analytics of the role as I was being pulled into meetings to discuss numbers I had crunched or was able hack together a tool to automate previously manual tasks.