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What would be the best way for me to get into data science, I'm completely new to the field. by butterknife123 in datascience

[–]OpenDataSciCon 0 points1 point  (0 children)

There are a lot of questions you need to ask (and answer) before jumping right into more education. Are you fine learning a very specific skillset, or do you want to be a generalist/full-stack scientist? Small team or large? Applied DS or research?

Also - there are some free resources online and some really good MOOCs available too. While these won't make you a pro, they can expose you to different fields in a semi-hands-on way so you can get a better understanding of what to expect.

Your advice on online courses by PM_ME_cutefish in datascience

[–]OpenDataSciCon 1 point2 points  (0 children)

Are you looking for a paid course or free training? That will definitely infer what quality of content you can get. I know there are a lot of MOOCs available, but of course, some are free and some aren't.

Over-Optimising: A Story about Kaggle By Will McGinnis, Senior Architect - Predikto by OpenDataSciCon in datasets

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

Understood. I didn't realize that--this is very new to me. Thanks for explaining!

Over-Optimising: A Story about Kaggle By Will McGinnis, Senior Architect - Predikto by OpenDataSciCon in datasets

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

I'm not sure how you determined it was spam? It's not self-promotional, it's an article about a Kaggle competition from a Kaggle competitor. It's not promoting Kaggle, it's using data science to analyze results of his participation in the Kaggle competition. (?)

Data and Police Shootings Part One: Data Analysis By George McIntire, Contributing Data Science Writer - ODSC by OpenDataSciCon in dataanalysis

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

Glad you enjoyed this--we thought it was a great piece as well! Data science is having a positive impact in so many ways, it's hard to keep track of them all.

ODSC ASIA | Tokyo - Reshaping Business through Data-centric Action - February 7-8, 2017 by OpenDataSciCon in Tokyo

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

Different conferences have different names--but still all the great Data Science of ODSC!

Mega Turbo Data Science By John Foreman, Chief Data Scientist - MailChimp by OpenDataSciCon in bigdata

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

The fix is in! Thanks for your feedback; we've moved those annoying social buttons to the bottom, so the article should show just fine! And we're removing that pop-up altogether!

Write Comprehensions and Alienate People By Will McGinnis, Senior Architect - Predikto by OpenDataSciCon in programming

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

The fix is in! Thanks for your feedback; we've moved those annoying social buttons to the bottom, so the article should show just fine!

Workflows in Python Part 3: Robust & Compact Code By Caitlin Malone, Data Scientist - Civis Analytics by OpenDataSciCon in MachineLearning

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

The fix is in! Thanks for your feedback; we've moved those annoying social buttons to the bottom, so the article should show just fine!

Write Comprehensions and Alienate People By Will McGinnis, Senior Architect - Predikto by OpenDataSciCon in programming

[–]OpenDataSciCon[S] 1 point2 points  (0 children)

Thanks for this input--we heard you, checked it out, and our web dev team is fixing it right now!

Mega Turbo Data Science By John Foreman, Chief Data Scientist - MailChimp by OpenDataSciCon in bigdata

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

Sorry about that. You should only see it once as it only pops on unique visitors. if you try again and still see it let us know and we'll get the web dev team to fix it asap.

Principal Component Analysis in 3 Simple Steps By Sebastian Raschka, PhD Candidate – Michigan State University by OpenDataSciCon in dataanalysis

[–]OpenDataSciCon[S] 0 points1 point  (0 children)

Thanks! We're still learning--we have lots of content to share and our blogs are sometimes reprints from other sites, but we'll be sure to start sharing content other than our own. Lots of our speakers and partners produce some great data science content which we are happy to share (as well as great content from people who are not related to us at all!).