Writing Functions in Python
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.
Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.
Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.
Learn how to analyze a SQL table and report insights to management.
Learn to retrieve and parse information from the internet using the Python library scrapy.
In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.
Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.
Data is all around us, which makes data literacy an essential life skill.
Learn how to manipulate and visualize categorical data using pandas and seaborn.
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.
Learn to use spreadsheets to clean, analyze, and draw insights from data. Discover how to sort, filter, and use VLOOKUP to combine data.
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Learn how to work with dates and times in Python.
You’ll learn how to (un)pivot, transpose, append and join tables. Gain power with custom columns, M language, and the Advanced Editor.
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Explore the world of Pivot Tables within Google Sheets, and learn how to quickly organize thousands of data points with just a few clicks of the mouse.
Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.
Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.
Build the foundation you need to think statistically and to speak the language of your data.
Data-driven organizations consistently rely on insights to inspire action and drive change.
Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.