abfazal1
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Hi all, would be grateful if I could get some insight on entry chancesfor the following MSc courses

MSc Statistical Science @ Oxford - https://www.ox.ac.uk/admissions/grad...stical-science

MSc Computational Statistics and Machine Learning @ UCL - https://www.ucl.ac.uk/prospective-st...e-learning-msc

MSc Statistics @ Imperial - https://www.imperial.ac.uk/mathemati...s/prospective/

My background

BSc Economics from LSE (completed 2013): First Class Honours, 79% in intermediate calculus and linear algebra courses in second year, 71%/72% in year 1 maths and stats courses, 63% in 2nd year econometrics, 68% in 3rd year econometrics (both econometrics courses were invovled multivariate regression analysis using linear algebra); winner of dept prize for year 1 exams, generally firsts or high 2.1's across all other courses (lots of mathematical content)

MSc Economics from LSE (completed 2020): High Merit overall with 71% average, 78% in pre-sessional maths and stats course (pre-sessional Stats course covers a lot of intermediate UG statistics but not Monte Carlo ), 67% in MSc econometrics course; top performer in economics of industry elective including top scoring dissertation (79% in both, dissertation was based on a theoretical/mathematical model); firsts or high 2.1's across all courses (as the BSc, lots of mathematical content)

Even through I don't have an academic background in maths/stats, my BSc and MSc were highly mathematical with a heavy focus on stats, regression analysis, calculus and linear algebra. Based on my review of the prerequisite material for Oxford or Imperial for example, I think I am covered in terms of background required before arrival. However, I have little to no coding experience in advanced software packages at the moment but am willing to put in the prep work (through online R courses for example) in the summer prior to starting (planned for Sep 2023).

I work in a technical economic consulting job where I would typically use Stata and maybe some SQL but there is a growing need for data science skills and I would really be pursuing any of these courses to upskill/future proof my career as part of an arranged sabbatical from work.

Grateful if anyone has useful input as this will somewhat inform how much effort I put in my applications/discussions with work etc. If there are other courses which you think have similar focus to the ones listed above, please also feel free to recommend!
Last edited by abfazal1; 1 month ago
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abfazal1
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Anyone, any thoughts?
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abfazal1
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bumping this up in case anyone has thoughts
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almost_th
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I don't really have any specific advice for any of the 3 courses you intend on applying to, but I'm currently doing an MSc in Data Science and Analytics at Cardiff University, and these were my observations having just finished the taught part of my degree with an 83%:

- You seem to have the required math background which admission boards place much more emphasis on than general programming skills. It's much easier to be lacking foundations in programming rather than math, by an absolute landslide even, and I believe universities are much more accepting of you lacking a bit of programming skills rather than math ones. In general, most languages used for teaching are R and/or Python (we've used both so far, unsure what the courses you're applying to require) which are pretty easy to pick up if you put enough work in. However, from what I've seen, a lot of students tend to go 'oh this is easy, I'll leave it till the last minute' for most programming/ML coursework which ends up killing their grades. Don't slack up there if you get in.

- Have you taken probability theory before? That class is perhaps the most useful one to know out of all the prerequisites (most universities say calculus/linear algebra + programming are the barebone prerequisites, but I'd add probability theory as an important one as well). Many of our cohort faced nightmares in our stats classes as they'd never touched probability theory before. Probability course is a fantastic website to brush up and/or learn some new stuff you're not familiar with. This was a lifesaver for me as I reviewed it extensively before starting.

Generally, I think you should be fine as your profile looks like someone universities would love to have on board. Best of luck in your applications!
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