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.

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

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

This course will equip you with all the skills you need to clean your data in Python.

Data Science Consultant at Lander Analytics

This course provides a basic introduction to Bayesian statistics in R.

Professor, Bowling Green State University

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

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

Director of Course Development at DataCamp

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

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.

Master fundamental techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Data Scientist at RStudio

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

Data Scientist and cofounder of Science Craft

Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.

In this course, you'll learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

Director of Training at Continuum Analytics

Learn how to build and tune predictive models and evaluate how well they will perform on unseen data.

Core developer and co-maintainer of scikit-learn; Lecturer at Columbia University

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

This course provides a comprehensive introduction to working with base graphics in R.

PhD in Electrical Engineering and Computer Science from M.I.T.

Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.

Chief Scientist at RStudio, author of ggplot2, dplyr, and tidyr

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

Assistant Professor at Smith College

This course was designed to get you up to speed with the most important and powerful methodologies in statistics.

DeWitt Wallace Professor of Mathematics, Statistics, and Computer Science at Macalester College

Learn how to parse data in any format. Whether it's flat files, statistical software, databases, or date right from the web.

This course provides a basic introduction to clustering and dimensionality reduction in R from a machine learning perspective.

Senior Data Scientist, Boeing

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Assistant Professor of Statistics at Reed College

Learn the language of data, study types, sampling strategies, and experimental design.

Associate Professor at Duke University

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Learn how to access financial data from local files as well as from internet sources.

Senior Quantitative Analyst and member of R/Finance Conference committee

Build the foundation you need to think statistically and to speak the language of your data.

Lecturer at the California Institute of Technology

Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Author of data.table

Further improve your Python data importing skills and learn to work with more web and API data.

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Data Scientist at Data Robot and co-author of caret

Learn more complex data visualization techniques using Matplotlib and Seaborn.

Software Engineer at Continuum Analytics and Developer of Bokeh

This course will show you how to combine data sets with dplyr's two table verbs.

In this course, you'll learn the basics of relational databases and how to interact with them.

Co-Author of Essential SQLAlchemy and Software Engineer

Use your data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Data Scientist, Stack Overflow

Learn the core techniques necessary to extract meaningful insights from time series data.

Assistant Professor at Cornell University

You will learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.

In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Data Carpentry instructor and author of nxviz package

Learn to create interactive analyses and automated reports with R Markdown.

Learn the bag of words technique for text mining with R.

Assistant Vice President of Innovation at Liberty Mutual Insurance

This course is all about the act of combining, or merging, DataFrames, an essential part of any working Data Scientist's toolbox.

Take your data visualization skills to the next level with coordinates, facets, themes, and general best practices in ggplot2.

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Professor of Statistics at the University of Pittsburgh

Learn to apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

Creator of xts and quantmod

Learn how to create versatile and interactive data visualizations using Bokeh.

Learn about how dates work in R, and explore the world of if statements, loops, and functions. You'll practice this knowledge u...

Learn how to build a model to automatically classify items in a school budget.

Co-founder of DrivenData

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

Director of Research at lateral.io

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Assistant Professor at Oregon State University

Learn the basics of the important features of the RStudio IDE.

This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Learn the practice of drawing conclusions about a population from a sample of data, a process known as statistical inference.

Professor at Pomona College

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Professional Quantitative Analyst and R programmer

Further your knowledge of RStudio and learn how to integrate Git, LaTeX, and Shiny

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

Professor of Finance and Econometrics at Vrije Universiteit Brussel and Amsterdam

Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Vice President at Compass Lexecon

In this follow-up course, you will expand your stat modeling skills from part 1 and dive into more advanced concepts.

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Instructor at DataCamp

Strengthen your knowledge of the topics covered in Manipulating Time Series in R with xts and zoo using real case study data.

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Analyst at DV Trading and co-author of PortfolioAnalytics R package

Use a rich baseball dataset from the MLB's Statcast system to practice your data exploration skills.

Assistant Professor at the University of Florida

Learn to visualize multivariate datasets using lattice plotting.

Professor at the Indian Statistical Institute, a member of R-Core, and the creator of lattice.

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

Quantitative trader and creator of thertrader.com

Learn how to make predictions about the future using time series forecasting in R.

Professor of Statistics at Monash University