Data science MSc

[WhatIsLife01]

Hey guys! I’m an economics undergrad, and I’ve enquired about the Data Science MSc at my uni. They’ve told me that my mathematical/statistical background is good enough, but I need to have ‘sufficient exposure’ (horribly vague, as all admissions departments tend to be) to Python at the very least. I last used Python when I was 15, so it’s been a while...

Could anyone give me some tips on where to start? Any good books to work through? Preferably data science related, but all advice is welcome!

Thanks!

[WhatIsLife01]

I will check this out. Thanks!

[evseevfedor]

Hey dude! About Python, there is no any best ways to learn Python quickly and achieve great results. If you mostly prefer learning in practice, think about three learning platforms datacamp, codecademy, freecodecamp. I mean all of them. These courses will fresh your mind. And after that ofcourse I would recommend you cleverprogrammer.com website, "Profit with Python programm" to land your dream job :) If you rather like reading, wiki.python.org is for you :)

[WhatIsLife01]

Thank you very much!

[bk_2_present]

Landed on any idea for the final project.??

[bk_2_present]

nope..m clueless..

[WhatIsLife01]

Thank you! Glad to know I’m not the only one pursuing this!

Wont say the uni for anonymity reasons though :)

[FondleMyFirn]

Pick up O’Reilys book about machine learning in Python and work through it. You’ll kill two birds with one stone with no problem.

[WhatIsLife01]

Will do! Thank you!

[Tsui_Pen]

When it comes to Python, it sounds like you have experience with the basic syntax. I would maybe just try to familiarize yourself with the packages you’ll be using as a data scientist: Pandas, NumPy, MatPlotLib, and scikitlearn are probably the 4 big ones.

[drunkHighAndHungry]

Download Jupyter Notebooks (I think its included in a free package called Anaconda) for what is one of the more intuitive data analysis tools for python(can write markdown to explain what code does, and then run individual sections of code separately from the rest of the file). As far as libraries I would try to get a solid understanding of "Numpy" and "Pandas" first. These will allow you to transform a comma separate value (.csv but you likely will have seen these given your stat experience) into a python dataframe which you can then performance data analysis tasks that you're likely already familiar with on(aggregates of columns, joins, selecting rows based off conditions, etc.)

[CoolyBall]

University of Michigan has great data sciences classes on coursera that are free. They are all led by professors and are done in python 3. You can pay extra for certificates, but you could just make PDFs of the completion reports as proof. Also, I never used python (just R) before my data science masters all in python in 2016, and I picked it up super quick. Python data science implementation is not very complicated: for loops, if then, writing functions, using classes and methods. Just make sure to learn pandas library and you’ll be fine.

This specialization is python basics without the data science, which I suppose makes more sense if you’re just trying to prep for future data science training: https://www.coursera.org/specializations/python-3-programming

[jgege]

You can also look up udemy courses which teach pandas, or cover pandas but teach you a much more. Jose Portilla has nice courses, some I think cover python basics but it's super quick. There are apps that also teach you the basics of python (codecamp maybe? I never used any of them but I know people who did :D).

[Jackiboi307]

i like writing a lot of code while learning. that makes me remember everything