– Big Data startups • Wide-range of techs – Database systems – Programming languages • Developer relations • University relations • 10 books, many presentations
21st century, and are so in demand that there won’t be enough of them to fill every position by 2018, according to a report by McKinsey Global Institute. How to help fill this demand and become a Rockstar Data Scientist? Abstract
Collec7ng data sets Mining data for pa<erns Other Refining algorithms Building training sets How a data scientist spends their day Source: http://visit.crowdflower.com/rs/416-ZBE-142/images/CrowdFlower_DataScienceReport_2016.pdf
Collec7ng data sets Building training sets Other Refining algorithms Mining data for pa<erns What’s the least enjoyable part of data science? Source: http://visit.crowdflower.com/rs/416-ZBE-142/images/CrowdFlower_DataScienceReport_2016.pdf
Machine Learning 5. Text Mining / NLP 6. Data Visualization 7. Big Data 8. Data Ingestion 9. Data Munging 10. Toolbox Source: http://nirvacana.com/thoughts/becoming-a-data-scientist/
– Specialized skills and business knowledge • Growth in self-service data preparation – Visual exploration with immediate feedback • Growth in advanced analytics platforms – IBM Watson
data science software – pandas, numpy, scipy • SQL – Used for relational and non-relational • Kaggle or equivalent – Get experience – Look at solutions
Online courses – edX, Coursera, Udacity, ... – Audit the courses, gain knowledge • Bootcamps • Master’s or PhD – Many data scientists have advanced degrees • Build your online portfolio