Maybe you’ve heard enough about this lately. But if you’re trying to learn data science, whether with Python or R, this is a chance to do it with something very timely.
The European Centre for Disease Prevention and Control publishes new data daily here in csv, xml and json format. It also includes some R code for reading it.
This site has some basic Python code to help you get the data and put it into a data frame with pandas. If you don’t know any pandas, it’s a great way to work with tabular data in Python.
So knock yourself out, and let me know if you find something interesting.
RealPython has some good stuff and is worth checking out. No, they didn’t pay me to say that – I’ve never made a dime for any such plugs (not that I wouldn’t take money , I’d just disclose that I did).
Here’s the link: https://realpython.com/free-courses-march-2020
Not sure how long this will be available, so check it out soon.
It’s true that all models are wrong, but some are useful. If nothing else about this model is useful, you can see an example of what can be done with R and Shiny.
Click around on the site and you’ll even find a Github link to the source code. Alright, here it is: https://github.com/alsnhll/SEIR_COVID19
A real trove here, and in multiple languages: https://github.com/EbookFoundation/free-programming-books
There’s much more free stuff on Github. You can scrounge without an account, but you can get a free account anytime. Some online courses have you submit your homework with Github, so you want to learn how to use it anyway.
I haven’t had time to look it over, but Google says they’ve indexed a lot of datasets for you to discover. They’re not all free, but if nothing else you know that they exist if they’ll help you scratch an itch. Look here for more info.
I just found out about it today, and it ends tomorrow. https://courses.linuxtrainingacademy.com/kindle-books/
This material is from Jason Cannon, who offers cheap training via Udemy and more expensive training with his own classes. I’ve never taken his full price classes, but I’d consider it, because he’s done a terrific job with what I have seen.
What have I seen? His Udemy classes on vim and Linux. I learned vim many years ago when I found myself having to use a Unix server regularly, but I picked up so many more useful tips from his docs and demonstrations. The Linux class was useful too.
This one is expensive, but sounds interesting: https://courses.linuxtrainingacademy.com/lrw/
What I’ve seen of his Linux training focuses on Centos, which is similar to openSUSE, which is common in enterprise settings. But there are countless other flavors of Linux, along with people willing to argue forever about which is the best.
If you have a Mac you already have unix, so there’s no problem learning basics and scripting. Obviously it’s not a problem if you are already running Linux. But Windows 10 users can play with Linux too, and on the cheap – check into the Windows Subsystem for Linux
Why Linux? You’ll find out, trust me…
Packt is offering two ways to get your cheap book fix.
Mega-Bundles consist of books selected around a theme, 15 for $50.
Build your own bundles are 10 books for $40. There is a great variety to choose from, including everything this blog discusses and much more besides.
Some of the books are shortish – 100 pages or so. You can see the page counts for the individual books. Of course length and quality are two different things.
Time may be short, so check these out soon. If you recommend particular books, leave a comment.
About now a lot of people look back on the past year and plan for the next. How about you? Are you closer to where you want to be, whether with data science or anything else in your life?
Tim Ferriss used to do new year’s resolutions, but no more – now he does a past year review. I’ll be doing it myself. Done right, it should wind up generating a list of things for you to emphasize for next year.
How was your past year of learning data science? What will you be doing about it next year?
“A goal is a dream with a deadline”. Set some deadlines if you’re serious. But be SMART about it.
Learning data science can take a lot of time. Know yourself. If you’re not going to follow through, maybe your time is better spent on other things. Far be it from me to discourage you – this blog is about learning data science after all.
But this is your life we’re talking about. If you can’t make yourself do the work, maybe data science just isn’t you. But then what is?
Mark Manson is opinionated and his language isn’t for everybody. Can he help you find a life purpose? How about Tom Bilyeu? Simon Sinek? Find your why.
It seemed odd to me that people wouldn’t know what they really wanted until I started questioning myself. Next time you’re zoning out with Netflix, some game, stuffing your face, getting buzzed, or whatever else is sucking the hours your life away without advancing toward your goals, think about this.
There are many sources of course work for R and other data science topics. I haven’t tried Business Science but it’s hard to resist free. Even if you already know the stuff it can be useful to have it presented from another perspective with different examples, especially if you don’t use it very often and are subject to getting rusty.
Yeah, they’ll pitch paid products at you – they *do* have to make a living.
So check it out here.
According to SAS, right here.