This course covers the different selection models in Qlik, including the click, legend and lasso selections and the associative selection model, as well as the role of smart search, the Qlik Sense cognitive engine and default and alternate states.

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Analyzing trends and patterns can unlock the power of data. This course will teach you to identify patterns and make informed predictions, enhancing your ability to analyze trends and make strategic decisions based on empirical evidence.

Learn to use the Census API to work with demographic and socioeconomic data.

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Discover applied machine learning techniques, focusing on deep learning applications for solving real-world problems in industry settings.