Master the basics of data analysis in Python. Expand your data science skill set by learning scientific computing with numpy.

Data Science Instructor at DataCamp

Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.

Co-founder and CEO of DataCamp

Level up your Python data science skills by creating visualizations using matplotlib and manipulating data frames with Pandas.

Continue your journey to become an R ninja by learning about conditional statements, loops, and vector functions.

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.

Data Scientist and contributor to the Keras and TensorFlow deep learning libraries

Learn to train and assess models performing common machine learning tasks such as classification, regression and clustering.

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Data Scientist and cofounder of Science Craft

Learn more complex data visualization techniques using Matplotlib and Seaborn.

Software Engineer at Continuum Analytics and Developer of Bokeh

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

Data Scientist at DataCamp

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

Learn to explore your data so you can properly clean and prepare it for analysis.

Director of Course Development at DataCamp

Learn how to visualize time series in R, then practice with a stock-picking case study.

Quantitative Trader and creator of the R Trader blog (www.thertrader.com)

Learn to visualize multivariate datasets using lattice graphics.

Associate Professor at the Indian Statistical Institute, member of R-Core, & the creator of l...

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