What I learnt in my first term on the BSc Economics, Finance and Data Science programme

My undergraduate expectations vs reality

• Programme content - the programme has not only met but far exceeded my expectations. It is tremendously well thought out and organised, with my first term presenting a unique and challenging blend of data science, probability and statistics, key economic issues and mathematics.

• The unique combination - combining economics, finance and data science into one single degree allows you to explore each one in much greater depth than if they were studied siloed from each other. For example, if you wanted to investigate a hypothesis you had about an economic issue, testing that hypothesis empirically against real-world data is a must – and for that, you need data science skills. 
  
  These subjects naturally cross-fertilise and buttress one another and learning them together makes you a better-rounded graduate and more competitive in each individual field. It is this interdisciplinary approach that aids your understanding and ability to translate your study into practice, which ultimately is the optimum way to learn anything.
   
• Workload - university learning is much more independent than at school and college – it is up to you to manage your time. I would say that, as long as you stay organised, you will be able to balance everything and keep up with the workload. Aim to review lecture notes if needed to cement understanding.  And don’t worry if it takes a little bit of time to get adjusted. The first term moves quickly but stay calm and organised and you won’t fall behind.
   
• Moving away from home - before coming to Imperial, I had always lived in England but never in London – so moving to the capital for my studies was an exciting change.  Adjusting to London and university life takes a second. You’re now having to balance your workload on top of essentials like food shopping, cooking, cleaning and commuting – for most of us, this is our first time doing so. However, you will learn to thrive and become a more independent person through the experience.  
  
  I found that the best way to adapt was to find a way of doing things that worked for me. For example, I choose to cycle to Imperial instead of taking the tube, which is quicker, cheaper and healthier. And whilst I’ve always enjoyed cooking, I’ve made a lot of progress in this area – I love trying recipes from scratch that I’ve never made before.

• Student life - I have engaged with Imperial’s many extracurricular opportunities while here. For example, the Algorithmic Trading Society, which relates very nicely to both data science and finance. I am a regular attendee of Muay Thai and the History Society and took an introductory course in CAD and robotics. Being surrounded by many of the world’s most promising engineers and scientists is an opportunity not to be missed either.

First term learnings

The first term is comprised of four modules, which give you a good foundation for the rest of the degree:

• Module 1: Big Issues in Economics and Finance - this module does exactly what it says on the tin. Each lecture focuses on a key contemporary issue in economics and finance. The key economic models are explained rigorously, and it also focuses on recent developments and how these issues are relevant to today.
   
• Module 2: Probability and Statistics – here you will learn an array of necessary skills, from probability theory to statistics.
   
• Module 3: Introduction to Data Science - this module introduces programming in R and teaches various data science concepts with a very practical approach.
   
• Module 4: Mathematical Foundations - this focuses on logic, set theory, real analysis, vector spaces and linear algebra and multivariable calculus. It’s fast paced and is particularly innovative as it uses generative AI to produce plots to visualise concepts.

My academic growth so far

My understanding of economics, finance and data science has already evolved hugely over the first term. We have covered a huge array of economic and financial issues, from the potential outcomes framework in random controlled trials to a fascinating guest lecture by Professor Jonathon Haskel on the importance of expectations in combatting inflation.

I have developed a greater understanding of the holistic process of data analysis, from the initial exploration of datasets all the way through to presenting our findings.

The programme does a great job of developing your understanding of the different subjects in tandem with one another, allowing for a cross-fertilisation of skills that will be invaluable in the future.