As a data science journalist, Karlijn writes for the DataCamp community, focusing on data science education, the latest news and the hottest trends. She holds degrees in Literature and Linguistics and Information Management.

Make your own neural networks with this Keras cheat sheet to deep learning in Python for beginners, with code samples.

The 150+ companies, resources, and tools defining the data science industry.

A beginner's guide to Spark in Python based on 9 popular questions, such as how to install PySpark in Jupyter Notebook, best practices,...

This PySpark cheat sheet with code samples covers the basics like initializing Spark in Python, loading data, sorting, and repartitioning.

Get introduced to the basics of correlation in R: learn more about correlation coefficients, correlation matrices, plotting correlations, …

Learn the basics of Exploratory Data Analysis (EDA) in Python with Pandas, Matplotlib and NumPy, such as sampling, feature engineering, co…

This cheat sheet is a quick reference for data wrangling with Pandas, complete with code samples.

A discussion of the evolution of and some of the key differences between IPython and Jupyter.

The differences between data engineers and data scientists explained: responsibilities, tools, languages, job outlook, salary, etc.

This Matplotlib tutorial takes you through the basics Python data visualization: the anatomy of a plot, pyplot and pylab, and much more

This Matplotlib cheat sheet introduces you to the basics that you need to plot your data with Python and includes code samples.

A SciPy tutorial in which you'll learn the basics of linear algebra that you need for machine learning in Python, with a focus how to with…

This Python cheat sheet is a handy reference with code samples for doing linear algebra with SciPy and interacting with NumPy.

Learn how to read and import Excel files in Python, how to write data to these spreadsheets and which are the best packages to do this.

This infographic shows the differences between Python web development and data science and how you can make the switch between the two.

A NumPy tutorial for beginners in which you'll learn how to create a NumPy array, use broadcasting, access values, manipulate arrays, and …

This Python cheat sheet is a quick reference for NumPy beginners

Discover how to create a data frame in R, change column and row names, access values, attach data frames, apply functions and much more.

What you need to do according to the data to get your H-1B visa certified.

A handy scikit-learn cheat sheet to machine learning with Python, including code examples.

An easy-to-follow scikit-learn tutorial that will help you to get started with the Python machine learning.

A handy cheat sheet to interactive plotting and statistical charts with Bokeh

A list of Python resources for the eight statistics topics that you need to know to excel in data science

Learn how to install, run and use R with Jupyter Notebook and RStudio's R Notebook, including tips and alternatives

This tutorial explains how to install, run, and use Jupyter Notebooks for data science, including tips, best practices, and examples.

An 8-step guide to becoming a data journalist, complete with tools, resources, and tips.

A quick guide to the basics of the Python data analysis library Pandas, including code samples.

A Pandas tutorial that covers the top 11 questions that users have about DataFrames in Python

Start your data science journey now and follow these 8 steps to learn data science.

This handy one-page reference presents the Python basics that you need to do data science

Get started on extracting insights from texts in R and Python with these 8 tips.

Discover why and how Open Data Science Conference (ODSC) can jumpstart your data science career

Data science resources you haven't considered (yet) - The best projects, tutorials, talks, podcasts, webinars, books, and much more to lea…

Discover how to create a list in Python, select list elements, the difference between append() and extend(), why to use NumPy and much more.

This infograph compares the roles of data scientists, data analysts, data architects, data engineers and more in the data science industry.

A tutorial on importing data into R. The focus is on reading data from sources like statistical software, databases, webscraping, and more.

There are different types of R plots, ranging from the basic graph types to complex types of graphs. Here we discover how to create these.

Comprehensive and easy R Data Import tutorial covering everything from importing simple text files to the more advanced SPSS and SAS files.

Wondering whether you should use R or Python for your next data analysis post? Check our infographic "Data Science Wars: R vs Python".

R Tutorial on Reading and Importing Excel Files into R. Understand how to read and import spreadsheet files using basic R and packages.

This small tutorial is meant to introduce you to the basics of machine learning in R: it will show you how to use R to work with KNN.

Learn how to make a histogram with ggvis. Go from the very basics to creating interactive graphs with shiny to display distributions.

Learn how to make a histogram with ggplot2 in R. Make histograms in R based on the grammar of graphics.

Tutorial for new R users whom need an accessible and easy-to-understand resource on how to create their own histogram with basic R.