Connect Tny and Coursera: Data Science Specialization to Build Intelligent Automations
Enable Integrations or automations with these events of Tny and Coursera: Data Science Specialization
Enable Integrations or automations with these events of Tny and Coursera: Data Science Specialization
Actions
Shorten URL
Generate a Tny shortened link from a provided long URL and return the short URL.
Unshorten URL
Unshortens a URL. Follows all redirects and returns the final destination of a URL.
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Frequently Asked Questions
To start, connect both your Tny and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in Tny triggers actions in Coursera: Data Science Specialization (or vice versa).
Absolutely. You can customize how Tny data is recorded in Coursera: Data Science Specialization. This includes choosing which data fields go into which fields of Coursera: Data Science Specialization, setting up custom formats, and filtering out unwanted information.
The data sync between Tny and Coursera: Data Science Specialization typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Tny and Coursera: Data Science Specialization. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Tny
Tny is a powerful URL shortening service designed to simplify link management and enhance online marketing strategies. With Tny, users can easily create, share, and track shortened URLs, making it an essential tool for digital marketers and businesses looking to optimize their online presence.
Learn MoreAbout Coursera: Data Science Specialization
Master the art of data science with Coursera’s Data Science Specialization, created by Johns Hopkins University. This program guides you through the full data science pipeline—from data wrangling and statistical analysis to machine learning and data visualization—using R and real-world projects.
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