Learn about data science for managers and businesses and how to use data to strengthen your organization.
An introduction to data science with no coding involved.
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Learn how to write unit tests for your Data Science projects in Python using pytest.
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
In this course you'll learn how to use data science for several common marketing tasks.
Discover how data engineers lay the groundwork that makes data science possible. No coding involved!
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.
This course will show you how to integrate spatial data into your Python Data Science workflow.
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.
Learn how to build a model to automatically classify items in a school budget.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Use C++ to dramatically boost the performance of your R code.
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
Learn how to approach and win competitions on Kaggle.
In this course you'll learn how to create static and interactive dashboards using flexdashboard and shiny.
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.
Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.
In this course, you'll learn how to import and manage financial data in Python using various tools and sources.
Visualize seasonality, trends and other patterns in your time series data.
Learn how to pull character strings apart, put them back together and use the stringr package.
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.
Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.
In this course you'll learn to build dashboards using the shinydashboard package.
Learn to combine data from multiple tables by joining data together using pandas.
Learn to retrieve and parse information from the internet using the Python library scrapy.
Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.
Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Learn to build pipelines that stand the test of time.
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.
Learn how to import and clean data, calculate statistics, and create visualizations with pandas.
Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.
Take your R skills up a notch by learning to write efficient, reusable functions.
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.
Use data science to catch criminals, plus find new ways to volunteer personal time for social good.
Discover the top tools Kaggle participants use for data science and machine learning.
Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie and TV data.
Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie and TV data.
Process ingredient lists for cosmetics on Sephora then visualize similarity using t-SNE and Bokeh.