End of Term

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It’s the run up to the Xmas break and there’s only a couple of days to go before we can take a much deserved breather.

The last 4 weeks have had an amazing sort of intenseness to them, filled with equal parts excitement and exhaustion. From past experience I know it is these intense times of hard work that linger in my mind as being the most rewarding, and so I’m sure that this period of time will be something I look back on and see as a pivotal point of growth for years to come.

Building on the foundations that we’re laid in the first half of term, our current courses have become progressively more technical and involved as we begin to work with real world data sets and to apply knowledge and techniques taught across modules.

So what are our classes like and what real world data sets have we been using?

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Optimisation

Our lecturer for Optimisation, Professor Wolfram Wiesemann, has an infectious enthusiasm which makes classes light hearted and fun. He has taken the time to devise a scheme in which every week we are given an optional (and more difficult) prize question alongside our regular homework. Here, the lovely Philipp Dufter, Joachim Ernst, and Jonathan Zimmermann can be seen proudly collecting the first round of Optimisation Prizes:

For me, there’s something very satisfying about the idea of optimisation; I love learning how to make an otherwise subjective decision making process objective. We have so far covered linear, discrete, and non-linear optimisation and we have been solving problems using Excel, AMPL, and GAMS (the latter two are specialist optimisation tools). We have been told AMPL licences can cost companies into the 6 figure mark, a fact which demonstrates the enormous value industry places on optimisation as a cost reducing tool.  In our most recent coursework we have been working with real world stock pricing data from the top 10 FTSE companies and putting together optimal portfolios according to desired risk levels.

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Network Analytics.

The modules primary objective is to teach different network analytics tools and methods. Its secondary objective is to develop our Python programming skills in preparation for next terms modules and our future careers.

For me, this has been an extremely relevant module; I’m currently in talks with a great guy from a social network start up called 6Tribes (whom I met at a start-up speed networking event last month in the Business School). He’s told me they have some very exciting audience and analytics roles, which I may potentially take on come June.  I can see the things we’ve been learning in this course (for example network community detection) could be very helpful in this role.

Our last coursework involved analysing a real world network of friendships within The Karate Club – a network in which two influential people fell out, causing the network to fraction into two parts. As part of our analysis we used packages in Python to detect communities so that we could predict how the Club would fraction. We also used different methods to compare our predictions against the Ground Truth.

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Very Large Data Management:

The unusual name for this module came from Professor Kalyan Talluri. He explained during induction week that the module could very well have been called Big Data Management if it weren’t for his aversion to the Big Data buzz words which are overhyped and shrouded in mysterious meaning. After all, how big does big data have to be to be Big Data?

VLDM has given us an overview of various Data tools including SQL, Hadoop, Spark, and Cloud Computing.

In the last couple of weeks, we have learnt how to set up remote clusters on Amazon Web Service and to communicate with them using our computers terminal. We have then used these clusters to apply a tool called Elasticity MapReduce in order to obtain insights from a large 30GB load of song play data from Last FM.

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Apart from the awesome course Xmas Party (which our event reps, Fabaiha Farooq and Jonathan Zimmermann organised for us at a swanky bar in the financial district)  there hasn’t been much time for socialising recently so I’m REALLY excited about our trip to Winter Wonderland on Friday to commemorate our first term

I’ll be back with another blog post in the new year when we start the next step of our analytics journey. Enjoy your holidays!

Holly is studying for our MSc Business Analytics programme.

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About Holly David

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