A Day in the Life of a Data Scientist

Hi there, it’s Tuesday! And we’ve got some exciting content for you to see. Kicking off with: the case for Python in scientific computing… [DataCamp]( DataCamp Weekly Issue #23 ― November 14, 2017 Hi there, it’s Tuesday! And we’ve got some exciting content for you to see. Kicking off with: the case for Python in scientific computing, a guide to Environment Variables, logistic regression implementation and more! There’s also a very cool data visualization at the bottom of this email made with high def satellite imagery and R. Enjoy! Like what you’re seeing? Forward to a friend! Received this email from a friend? [Sign up]( for a DataCamp account to to receive a dose of data science every Tuesday. Projects & Resources [Why Use Python Scientific Computing]( Discover the scope of Python for research, why scientists should use Python for scientific computing and how the Python community can effectively aid scientific research. Great post by DataCamp’s Hugo Bowne-Anderson. [datacamp.com]( [A Data Scientist's Guide to Environment Variables]( As a data scientist, you might have to configure environment variables for data science projects locally or globally, on a platform. This guide, by DataCamp instructor [Eric Ma]( will show you all you need to know about Environment Variables! [datacamp.com]( [Automating Summary of Surveys with RMarkdown]( This very helpful guide shows you how to automate the summary of surveys with R and R Markdown using RStudio. This will work great with static portions of a document. Which makes sharing a report more efficient and easily reproducible. Great read! [r-bloggers.com]( [The 10 Statistical Techniques Data Scientists Need to Master]( A handy overview of 10 statistical techniques that data scientists need to master. From linear regression to classification and tree-based methods, this post shows what to learn and why! [towardsdatascience.com]( In the News [Live Coding Recap: Frequencies of Words in Novels]( DataCamp instructor [David Robinson]( just launched a new DataCamp course last week. Here, David explains where the idea for this course came, why we believe it will have a strong impact, and a sneak peek into what is coming next. [varianceexplained.org]( [Implementing Logistic Regression using Titanic dataset in R]( DataCamp user abhaypadda shows you how to implement logistic regression in this blog post using the famous Titanic dataset. Interesting post that outlines the basics of logistic regression as well as its implementation. [analyticsdefined.com]( [Getting hyper-local: Mapping street-level air quality across California]( Google measured air-quality data using Google Street View cars in three Californian cities. The results are beautifully displayed and explained in this post. We look forward to seeing more cities mapped by Google soon! [blog.google]( Elsewhere • [When Will Demand for Data Scientists/Machine Learning Experts Peak?]( • [From Data to Deployment – Full Stack Data Science]( • [A Day in the Life of a Data Scientist]( • [Drawing 10 Million Points With ggplot: Clifford Attractors]( Jobs • [Data Scientist for H Labs, Chicago]( • [Data Analyst - Marketing Insights & Analytics, WeWork, Buenos Aires]( • [Data Scientist, WalmartLabs, Bangalore]( The United States mapped by over 1000 million acres of trees and forests More close up pictures available and an explanation of how this was taken and processed (using R!) if you follow the link. That's all for now. Have a great week! [DataCamp] [DataCamp]( DataCamp Inc. | 2067 Massachusetts Avenue | Cambridge MA 02140 [Facebook] [Facebook]( [Twitter] [Twitter]( [LinkedIn] [LinkedIn]( [YouTube] [YouTube]( [Unsubscribe](