Some testimonials of students (various languages incl Chinese, German and English)
- My question is not handled in the FAQ. What shall I do?
Feel free to contact the course director via [email protected]. If you are already a MISCADA student, please consult the internal Sharepoint pages beforehand.
- Can you please provide me with … for my ATAS clearance/visa documentation?
We cannot provide you with any documents for visa purposes. For general queries regarding the programme, please contact the admissions team. Do not contact the course director, head of departments, etc. It is the admissions team that will be able to help. ATAS itself however is ran by the government, i.e. please consult the government website for ATAS.
- I have applied successfully to program G5K609, but I can’t find any module description for it.
The module G5K609 is our old, generic MISCADA code where you pick your specialisation throughout the academic year. Today, we have different programme codes for the individual specialisations: For those students who did apply to the generic programme code, we will thus ask you which specialisation you want to pick, and you will then study exactly the same curriculum as the specialisation-specific codes.
- I had applied for MISCADA before but was not accepted. Can I re-apply?
You can always re-apply for MISCADA – in particular if you’ve done further courses meanwhile – but we will consider previous years of completed study and make them inform our decisions. If in doubt, feel free to contact the central admissions team.
- I’m really interested in machine learning and neural networks. So is this the right course for me?
MISCADA is about scientific computing and data analysis, i.e. we do cover ML but we focus not exclusively on it (we are also interested in simulations), we apply them to particular scientific problems, and we really dive into the foundations behind ML. If you want to see how we interpret ML and neural networks, have a look at this article. Though written by colleagues from another University, it sets the tone how we work in our course. If you search for a less theoretic approach to ML, then MISCADA is not the right course for you. A good test whether you are a fit to MISCADA is (a) to check that you are interested in science (and not just applying techniques) (b) to validate whether you consider yourself to be strong in C and Python programming and (c) to ask youself which specialisation you’d pick.
- I want to do the finance stream. Do I have the right qualification?
We do recommend our finance stream only for students with a math undergrad degree. You can do it with another degree, but you need a really good background in mathematics (in particular statistics) to be successful.
- What are the admission rates?
ATM (2022/23), we do not impose any quotas on the specialisations in astrophysics and environment and earth sciences, i.e. if you meet the formal requirements you will be admitted. There might be quotas on the financial mathematics stream. You have to contact central admission for details on this.
- I am not interested in physics or another specialisation, but in data analysis in … Can I do the course without the specialisation?
No, you can’t. If you are not interested in the specialisations and if you don’t have background knowledge in the specialisation area, then this is the wrong course for you! We target students interested in Physics or finances. The latter cohort need a very strong maths background.
- Where do graduates work?
Most of our graduates work in R&D divisions, compute centres or stay in academia. After all, we want to educate the next generation of researchers. Around 10% of our graduates continue with a PhD.
- Who teaches the individual modules?
The core content is mainly taught by experts from computer science and mathematics, though some modules in Core I are also championed by colleagues from physics. The exact assignment changes from year to year. For the specialisation modules, we ask experts from the respective domains and departments to read them. The overall programme thus is taught in a collaboration between the departments, while the core responsibility for the overall course resides within computer science.
- How can I collaborate with industry? Do you collaborate with industry at all if you are a (rather pure) science course?
Our prime goal first of all is to get the fundamentals right. We do however collaborate with industry when it comes to the dissertation. Terms 1 and 2 are reserved for fundamental skills and techniques as well as for the specialisation. In term 3, many students opt for a project together with an industry partner, while others prefer a more academic route to become prepared for a future PhD. See our example routes through the course (scroll all the way down on that page) or and the project remarks below. We also have prepared some success stories which might be of interest.
- How big is the student cohort?
It is always hard to predict the bums on seats, but we are heading for a class of around 10-20 students per specialisation.
- For the project […] do I […]?
A lot of students are interested in details around the project. Please see the dedicated project pages for information.
- Is there a reading list for …?
The curriculum tab on the top hosts some information about the different specialisations. Each comprises reading lists and remarks on general prerequisites for this particular specialisation stream. The generic prerequisites for MISCADA as a whole are discussed on the official sign up pages and a dedicated prereq page (see also FAQ entry below on most important skills), while there are no specific preps for the particular submodules within the generic part of the course that everybody has to do.
- Is technique/software XYZ covered in submodule Core …? Do we use … (insert MySQL, TensorFlow, Python or whatever you want) in submodule … (insert whatever you want)?
You might find information on the University’s webpages whether this particular topic has been covered in the previous year and/or used a particular technique. Usually however, these questions lead into the wrong direction. MISCADA covers fundamental concepts behind scientific computing and data analysis, i.e. behind the scenes, and from there illustrates how they are applied in state-of-the-art algorithms/software and the specialisation area. As MISCADA heads for a University degree, it is primarily about understanding concepts and methods rather than particular pieces of software or particular techniques. They might be outdated by the time you graduate. Your skills and knowledge will not. Therefore, we also change the toolset used in the course from year to year. Wherever we use specialised tools, we will introduce them throughout the course. What you need is:
- What is the most important skill I need to have (and to revise)?
There are three must-haves: programming in C, programming in Python and maths. If you are not “fluent” in the two programming languages (both of them!) you will struggle (see the prerequisites discussion). Fluent for us means you have to be able write proper, working code for complex challenges. But you don’t need knowledge in software engineering or the development of large software packages. Some basic knowledge of object-oriented programming helps; again, no need for fancy object-oriented programming patterns or advanced meta programming or … This is not a software engineering degree. So they don’t harm, but you don’t need them. Once more: You also need maths. A lot of it!
- Do you teach remotely?
All of our lecturers are recorded and made available for offline revision/learning, but we do not really provide an online option of the course, i.e. our default is, in line with the University guidelines, face-to-face teaching.
- What hardware requirements are there?
If you study in Durham, you have access to our labs and our library which are equipped with all computer resources that you’ll need. Most of our teaching however is based upon online servers and particular supercomputers, i.e. you don’t have to own specialist equipment – you just need a proper browser and an internet connection. We’ll take care for the right resources under the hood. If you want to work from home without an online server – which is something we encourage you to try out at least – you’ll have to take care of your machine yourself. See some remarks at the Prerequisites page.
- When do I select my specialisation?
You have to pick your specialisation when you register for the course. Each specialisation has its own programme code. Students can, within the first weeks, request the transition to another specialisation stream, but this is subject to approval by the management board.
- When and how do I select my modules?
See item above for comments about the specialisation. On the core side, there’s no choice in term 1. You have however modules to choose from in term 2. Durham’s registration will ask to you put in some choices when you sign up. This is only an indicative choice for us! Towards the end of term 1, the lecturers will pitch the individual core modules from term 2 and you will be able to ask further questions – at that point, you’ve attended the majority of term 1 lectures and you will thus have a good understanding of what the course contents mean. You then have till the first day of term 2 to decide which core 2 modules you want to take in term 2 and to revise and alter your initial selection.
- What Unix version/Linux distribution should I use, what C IDE should I use, what Python packages do you recommend, what is the best book to learn …?
Such detailed questions are very much a matter of taste, and we do in general never give support for your own IT device. Please safe the questions until you are enrolled. There will be a course-specific forum where you can ask your fellow students about their preferences. We do monitor this forum (to ensure that no totally wrong things are written there), but we rely very much on the cohort spirit to answer such questions.
- to be continued …