Change to data science Watch

giorgori
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Hello friends. Some info about my background: My first degree in in Psychology. Then I decided to do a generic MSc in Psychology again and it's when I came in touch with some basic research methodology. I learnt spss and a bit of R from the scratch and gained some experience on data analysis ( used regression, lots of Factor Analysis, some multilevel modeling on some quantitative projects).
I was keen quantitative analysis on research but didn't engage a lot after my masters cause I got a full time job in a hospital. Two years after, I have arrived to the realization that psychology is not for me and I cannot imagine myself on this field anymore. Having this in mind and considering the fact that I liked statistical analysis, I decided to apply for a MSc in data science and analytics of Cardiff University. Surprisingly, I was accepted even though the requirement was first degree on a numerical subject. To be honest I am very excited by this upcoming challenge but at the same time I'm also worried that I won't be able to pull it off. I have no idea about programming, coding and whatsoever and the particular course is full of python, machine learning etc.

Do you think that shifting from a theoretical field like psychology towards data science and programming is doable on my 30s? Is prior knowledge of Algebra, calculus necessary?
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HoldThisL
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Sure it's possible but have a closer look at the entry requirements.

Machine learning uses things like probability theory and other statistical techniques, a programming language (python being common), knowledge of linear algebra is always helpful

But if the course doesn't require that, you will be taught it, although that certainly sets a challenge
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artful_lounger
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You have more than enough time to learn the rudiments of at least one programming language before the course starts, assuming it begins in September/October. There is a lot of material online supporting people in self studying programming and learning programming languages; however if it doesn't state a requirement to have programming experience before then presumably they'll teach you anything they need to know,

I doubt you'll use calculus in such a course, although a general mathematical ability to at least GCSE level will likely be assumed. They may well assume you've studied calculus before given they normally expect a "numerate" degree, although I'd be surprised if you actually have to do any calculus on such a course. Looking at the course content, it looks like it won't be necessary, although a good background in other maths topics including algebra etc may be needed or helpful. You can see the reading lists on the course webpage by clicking each non-dissertation module and scrolling to the bottom, and then you could look at the contents of those books to gauge your preparation for that material.
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TCA2b
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I think you're best off contacting the university with any concerns you have about your current level of mathematical knowledge and what support they offer, if any. Here is a list of important subjects one of the universities I contacted provided with regard to their course in data analytics:

Expected mathematical knowledge

1.Ability to use a scientific calculator–capable of using and understanding functions such as exp, log, x^y on a calculator
2.Algebraic notation and manipulation; subscripts; simple results–you should feel comfortable manipulating equations and working with subscript notation. You should be able to solve a quadratic equation.
3.Logs and exponentials–you should have a general understanding of the use of logs and exponentials. You also need the ability to carry out logarithmic transformations and an understanding of the logarithmic and exponential laws of summation, division, etc.
4.Graphs of simple functions–you need the ability to draw and interpret graphs of simple linear and non-linear mathematical functions.
5.Differentiation (including differentiation of a product). The idea of a differential equation–you should have an understanding of when differentiation is used. Also the ability to carry out differentiation on different functions including functions that include the product of two variables. A basic understanding of how to solve equations that involve one or more derivatives is required.
6.An understanding of what integration is. Integration of polynomials and ex; integration by parts–you should have the understanding of when the use of integration is appropriate and the ability to carry out the integration of functions that contain variables with nonnegative integer powers.
7.Finite sums. Infinite sums of x^i and X^i/i!–the ability to carry out sums of arithmetic and geometric series. Ability to sum infinite series of elements that have the form ∑x^i or ∑x^i/i!, where, for example i−1 to ∞
8.Simple manipulation of vectors and matrices–you need the ability to carry out simple manipulation, such as addition, subtraction and multiplication of vectors and matrices.
9.Series-previous exposure to power series (i.e. Taylor/ Maclaurin series) and binomial series will be helpful (though no detailed knowledge is expected).
10.Statistics-previous exposure to standard probability theory and statistics (such as mean/mode/median and probability density functions, as well as random variables such as Poisson, Binomial or Normal) will be helpful (though no detailed knowledge is expected)

They go on to emphasise that they'd expect an understanding of 1-4 and 7 and an awareness of 5,6 and 8 but not a solid understanding.

As I said in the other thread you made, I'm in a similar predicament, and it's more a case of whether you can fill those knowledge gaps between now and when the course starts than whether it is feasible given your age (which is young) in the abstract.
Last edited by TCA2b; 1 month ago
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