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 skill set by learning scientific computing with numpy.

Intermediate Python for Data Science Level up your data science skills by creating visualizations using matplotlib and manipulating data frames 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.

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

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

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

Importing Data in Python (Part 1) 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.

Introduction to Data Visualization with Python Learn more complex data visualization techniques using Matplotlib and Seaborn.

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

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

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

Importing Data in Python (Part 2) Improve your Python data importing skills and learn to work with web and API data.

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

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

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

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.

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

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.

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

Introduction to Time Series Analysis Learn the core techniques necessary to extract meaningful insights from time series data.

Manipulating Time Series Data in R with xts & zoo The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

String Manipulation in R with stringr Learn how to pull character strings apart, put them back together and use the stringr package.

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

Sentiment Analysis in R: The Tidy Way In this course, you will the learn principles of sentiment analysis from a tidy data perspective.

Data Types for Data Science Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them t...

Object-Oriented Programming in R: S3 and R6 Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Writing Efficient R Code Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Data Visualization in R with ggvis Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

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