Holiday’s are for Becoming Awesome (with data)

Most of us have a wish-list of things that we want to lean, and for some of us, the christmas holiday’s might provide some time off work. Although this time is usually filled with family events centred around eating and/or drinking too much, there’s always a tiny bit of spare time.

So why not use that time to become awesome at [INSERT YOUR WISH FOR SANTA].

There’s a massive amount of free and low-cost data science courses available online at Coursera and other sites, so here’s a few to get you started (if you cant be bothered googling “data science free online course“):

Free

Paid:

Data’s just waiting for you

We’ve started to collate a page of decent data sources. It’s currently separated into international and Australian sources, and It’ll grow with time:

Links to data sources

If you’re looking for data in Australia, you can’t go past the 2015 list from the team at GovHack:

https://www.govhack.org/2015-data/

Cheat Sheets = Sweet Sheets

The geniuses at RStudio have a super-sweet set of cheat sheets for:

Shiny
- to build fully dynamic/interactive web apps, including interactive statistical models and output graphics.
Data Visualisation
- Explaining the super sweet ggplot2 package. ggplot2 can be a bit hard to understand at first, but this will definitely get you started.
Data Wrangling
- The dplyr and tidyr packages are must haves whenever you need to either reshape, transform or combine data sets. Think “split-apply-combine”: split the data, apply a function, then combine it back together, all at once, its GOLD.
Sharing R Packages
- Once you’ve got a handle on R, you might want to create your own packages, this one will get you on the way.
R Markdown & Reference
- R Markdown lets you create documents. Basically you write some code in R and export the results as html, pdf, or MS Word files.

All of the cheat sheets are on the RStudio website:

https://www.rstudio.com/resources/cheatsheets/

And then there was the beginning

The road to learning about analytics, statistics and data science is a long and sometimes treacherous path. The journey is full of moments of pure wonder and amazement, which are often followed (immediately) by confusion and despair.

I’m an Environmental Scientist with a long history of using GIS and have been excited about Statistics and Data Science for years. On my Data Science journey, I’ve meet a ton of exceptionally talented analysts, but I’ve noticed that they usually have a background in either IT, finance, marketing or biostatistics (probably because that’s where the money is…).

So I’m always surprised and super exited whenever i meet another Enviro/Geo/Earth Scientist/Engineer who’s on the Data Science bandwagon.

And one of these chance meetings just happened while admiring Mt Sturgeon, so we’ve setup this site to share what we learn in an effort to bottle up the enthusiasm and let it brew into something great (or at least have a list of cool things to remember).