Hi, so we're really pleased to be in The Deck today.
The Deck is this really cool new space, which the University has opened up to promote student start-ups.
So we're really keen on entrepreneurship. We want all the students to be developing cool ideas
and starting businesses so we've created a space that they can use to have meetings, to be inspired,
get round a whiteboard. There's even a ping pong table in the corner which you can't see.
So it's a really cool space for promoting student businesses really and we have a team of people
whose job it is to support those activities and try and get these businesses off the ground.
Hi, my name is Hywel Williams, I'm the Programme Director for MSc Data Science at the University of Exeter.
I'm here today with some of the students on the course so maybe do you want to go round the table
and introduce yourselves, so let's start here. Hi I'm Carolina, I'm 24.
My name is Simon Tucker. Weisi, I'm from China. I'm Jiajie, I'm also from China.
Ok, so these guys have taken some time off from their studies, they should be in the library working hard
but they've taken some time today to talk to us about why they came to Exeter.
So, I guess the first question, let's find out a bit about the background. So, guys, where were you
before you came here? What were you doing before you came to Exeter to study?
I was a student in China, I was majoring in Computer Science in a University.
I wanted to be here, because I needed some mathematical skills to compensate my skill set,
so yea, this is the reason. Ok, so how about you, Simon?
So, I have a bit of a different background to everyone else because my bachelors is in Chemistry.
So, this is quite a big change for me, but I did a small amount of Python coding while I was at uni.
which I kind of really enjoyed and then after uni I did a few different laboratory jobs
and realised I wasn't really into the whole laboratory kind of thing and I kind of prefer having a problem
or something to work on and also I've kind of seen a lot of very interesting Data Science things like
machine learning and stuff and I'd put a lot of spare time into doing stuff in Python anyway before I came here
So, you were a proper chemist in a white coat in a lab? Oh yea.Yea and you decided that that was not the thing
and you wanted to come and be a Data Scientist? Yea I really just don't like labs, it's just not my thing.
Alright, Weisi. What were you doing before you came here? Ok, well I graduated in 2015.
I had a bachelor's degree in Finance and after graduation I worked for a security company for two years.
I worked as a Investment Advisor. But you know, in China it's different.
You need a promotion, the least you need to get is a masters degree
and apart from this, you know the people who like the big data, they need some advice
based on the data but not just on some HRs.
So I guess this course is very suited to me, it ticks off a lot of stuff and basically suits my background.
Ok, well thank you, and Carolina?
I did a bachelors in Engineering and I worked in a bank for two years but then I moved to a Data Analyst job.
Then I found out that I needed to learn more about the topic and learn more about the theory behind it
so that's why I decided to go for a masters.
Ok, so we've got different backgrounds. We have: engineering, chemistry, finance and computer science.
And different countries, you guys here from China, from England and from Brazil.
So, we're quite international, we're quite diverse in backgrounds.
You've said a little bit about why you wanted to do a masters, but what about this Masters in Exeter?
Why did you come here and not somewhere else?
I think for me, it was an easy choice because it's very local and it's a well respected University as well
so it just happened to be really convenient.
Ok, so it was your local university but also a good University. And how about the guys who have travelled
from a bit further? So you've come all the way from Brazil and China, so why here?
well first of all, I think Exeter is a good place, especially for study and I think Exeter is very famous for
it's Business School so I think, that because my modules are in Data Science and Business
so I think I can benefit from it.
I came to Exeter for two reasons. First of all, it's one of the most technical projects of the whole UK.
Because, some of the business analytics programmes, most of them are based on the applications
but we've spent a lot of time on theories. And the second part was because my cousin also graduated from
Exeter as well, his major was in education and he recommended to me highly, so I believed him.
First of all, the University has a good reputation and also I'm doing Data Science with Business.
So, well I really liked the content of the course and you get the best of both worlds, so that's why.
And how has that gone for you? Do you find that balancing the data science with the business part
of the programme, does that work well?
Yea, I think so, well they're kind of complimentary you know. What you learn on the business side,
you can relate to what you learn in the Data Science side. So yea, it works well for me.
And, let's talk about the course itself. So obviously, you are now half-way through I would say.
You've done some of your taught modules, you're doing some more taught modules right now.
You're just about to start doing your research projects. I guess, what have you found the most
interesting and what have you found the most difficult? Let's go for the one you've liked the most
and how it was interesting and the topic that you've found most challenging. Let's see what you all say?
I think the most challenging? I have found Computer Vision the most challenging.
Because the maths in that is really difficult. I think it's very similar to Machine Learning really
in a lot of way because there's a lot of overlap, but it seems to be more maths heavy a lot of the time.
And then.. what was the other question sorry? So which one have you found most interesting?
Most interesting.. probably Machine Vision, actually.
So, it's the most interesting but also one of the most challenging?
Yea I think so. Well that must be good because it keeps you going when things are tricky. Yea.
How about anyone else? I think the most challenging and the most interesting is also the same thing for me
because I think the math, however tough the math is, is the most interesting
and the most challenging for me too because I didn't study too much math in my country
but this is what I'm here for so this is one of the most interesting things, yep.
Weisi? Well, for my part the most interesting is about one of my projects last semester.
It's about the analysis of twitter. Yea,  because it feels like digging gold from the mountains.
Because in my mind Data Scientists were doing this kind of job. We've got a lot of data, we find some
very valuable information from a lot of noise, so I find it very interesting.
I also thought about maybe we can find some investment advice on the inside and maybe
help my investors to make their product better. But the most difficult part is about math as well I believe.
I spend a lot of time understanding. So, Mathematics is involved in Data Science, there's no escaping it.
Alright, so Carolina, we didn't find out what your favourite modules were, what do your enjoy studying?
I'm really enjoying machine learning, it's a core module, a Data Science module.
Well, it kind of mapped to my expectations, I feel like I'm learning a lot there
and, well the hardest part for me is to balance the deadlines and deal with all the course work
and well, do it all in time.
Well, maybe we should talk about the projects. So what projects have you all signed up for?
Let's start with Carolina.
I signed up to Weather Prediction with you. Ok, well yea I guess I knew that! yea!
So what interested me in the project is the fact that I can use machine learning to real life situation.
So it's a chance to apply what we learnt.
Yea, so this project, I think it will be really cool. It's using natural language processing and networks
to try and find, well, to try and make weather forecasts I guess, by reading text and articles.
So that should be good fun. How about you, Simon?
I'm doing something really similar actually, it's natural language processing for emergency events.
I was kind of interested in it because we did a project involving data which had been taken
from Twitter and turning it into useful information and being able to see what people are actually
discussing the most and I found that interesting and so that's what I chose.
Ok, how about you both?
I chose the programme, it's the relationship between income and some parts of psychology.
So it's a nice applied data science project where you're taking some real world data and finding something out.
So, one final question then. When you get to graduation day, you're going to receive your certificate,
you'll get a nice ceremony and then what? What are you going to do next?
What is this MSc going to take you on to in your future?
I'm quite interested in looking at doing a PhD but I'm definitely going to take a few months off and then
start looking at that and then I'll think about getting a job if I can't find anything of interest.
Ok, so maybe a PhD for Simon. Carolina?
Well, I'm currently applying for jobs back home. I feel now  I'm more qualified to get a proper Data Science job.
So what do you think the MSc has given you, because you were working in Data Science before you came.
Yea. And then you're going to go back and working in Data Science. What do you think the MSc
will give to you, that you didn't have before?
Well now I'm able to understand the topic more broadly so I can take harder challenges in a job situation.
and also, before I was working more as a data engineer. So looking at data bases and collecting and cleaning data
so now I'm more interested in analysing data and getting insights from it using machine learning.
So you can use the data to answer questions now rather than just rearranging the data base. Yep.
Ok, well that's great. How about you guys?
Well for me, I'm applying to find a job at home as well. Basically I am looking for some consulting companies
or some advisory companies who use the data as a tool to help my client to place their investment.
And maybe perhaps I will look at trying to apply to some data analysis jobs in internet companies like AliBaba.
And you think the MSc is going to give you a good chance of getting a better job?
Yea, absolutely.
I'm planning to go back home also and I'm looking for a job related to data science.
As a Computer Science student I'm not interested in software developing or  hardware developing.
I'm quite interested in Data Science but before I go back I will try to get an internship or project experience here.
OK, great. Well, thanks very much guys.
Ok, we've had a question come in on Wechat, which is asking what should you do to prepare
or what book could you read before you come and start the course.
So, I'll recommend a book which I really like which is called 'Doing Data Science' by Cathy O'Neil
and Rachel Schutt. So that's an O'Reilly book from 2013. I think it's a really good introduction to Data Science
as an area. But let's talk to the students. So how did you guys prepare for the course before you came?
So, they use Python here quite a lot so I spent quite a lot of time learning Python and there's a really good website
I'd recommend which is hackarrank.com and they have lots of challenges , there's like thousands
for lots of different languages and I think I did about 90% of the Python ones
and they're slightly more challenging than a lot of the practise ones that are on a lot of other websites to be honest.
And I think R is quite an important language as well here, especially if you want to do the stats modules
but I think if you had to pick one then Python. And I kind of wish I'd brushed up on my maths a lot more
so, learning algebra and calculus are very important for Data Science I think.
Ok, and anyone else got any tips? Ok, I have three recommendations. The first one is about the Python skill
because I have never learned Python before so about three months before I came here I spent a lot of time
Data Camp, datacamp.com. Some of the modules are free, it's very useful.
The second part is maybe suitable for the Chinese student. There is a book written by a Chinese guy
called Zhou Zhihua and it's name is 'Machine Learning' and the people in China call it the 'Watermelon book'
because all of the examples are about watermelons.
Yea, it's a very interesting book.
The third one is about statistics. We should spend a lot of time and we should learn more about calculus and
and maybe about machine learnings so I recommend the open courses from MIT,
the linear algebra. I think it's just the most useful linear algebra course maybe all over the world.
Ok, we cover some of that stuff in the first modules as well, so you don't get dropped in
completely on your own. But anything you can do before you come is going to help.
I managed to survive so, I'm doing alright!
