Data Scientist with R A Data Scientist combines statistical and machine learning techniques with R programming to analyze and interpret complex data. Learn More

Data Scientist with Python A Data Scientist combines statistical and machine learning techniques with Python programming to analyze and interpret complex data. Learn More

Introduction to Python Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with numpy.

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

Intermediate Python Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

Python Data Science Toolbox (Part 1) Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

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

Supervised Learning with scikit-learn Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

Introduction to Deep Learning in Python Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.

Introduction to Data Visualization in Python Learn complex data visualization techniques using Matplotlib and seaborn.

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

Python Data Science Toolbox (Part 2) Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

pandas Foundations Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

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

Statistical Thinking in Python (Part 1) Build the foundation you need to think statistically and to speak the language of your data.

Intermediate Importing Data in Python Improve your Python data importing skills and learn to work with web and API data.

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

Data Visualization with ggplot2 (Part 1) Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

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

Introduction to PySpark Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Introduction to Data in R Learn the language of data, study types, sampling strategies, and experimental design.

Data Manipulation in R with dplyr Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Introduction to Git for Data Science This course is an introduction to version control with Git for data scientists.

Interactive Data Visualization with Bokeh Learn how to create versatile and interactive data visualizations using Bokeh.

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

Correlation and Regression in R Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

Merging DataFrames with pandas This course is all about the act of combining, or merging, DataFrames, an essential part your Data Scientist's toolbox.

Exploratory Data Analysis in R Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Introduction to Natural Language Processing in Python Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from ...

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

Statistical Thinking in Python (Part 2) Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Intermediate Importing Data in R Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

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

Network Analysis in Python (Part 1) This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

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

Data Visualization with ggplot2 (Part 2) Take your data visualization skills to the next level with coordinates, facets, themes, and best practices in ggplot2.

Machine Learning with the Experts: School Budgets Learn how to build a model to automatically classify items in a school budget.

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

Importing & Cleaning Data in R: Case Studies In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

Introduction to TensorFlow in Python Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

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

Exploratory Data Analysis in R: Case Study Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Foundations of Inference in R Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Unsupervised Learning in R This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

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

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

Building Dashboards with shinydashboard In this course you'll learn to build dashboards using the shinydashboard package.

Introduction to Deep Learning with PyTorch Learn to create deep learning models with the PyTorch library.

Biomedical Image Analysis in Python Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

Network Analysis in R In this course you'll learn to analyze and visualize network data with the igraph package.

Data Visualization with ggplot2 (Part 3) This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Foundations of Functional Programming with purrr Learn to easily summarize and manipulate lists using the purrr package.

Introduction to Bioconductor Learn to use essential bioconductor packages using datasets from virus, fungus, human and plants!

Network Analysis in Python (Part 2) Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Data Exploration With Kaggle Scripts In this course you will begin learning the art and science of data exploration. You'll also become familiar with some...