
When this happens...
Automatically do this!
Enable Integrations or automations with these events of MagicalAPI and Coursera: Data Science Specialization
Gets profile data from LinkedIn using the provided username.
Retrieves company information from MagicalAPI using name, LinkedIn username, or website.
Generate a single score that shows how well a resume matches a job description.
Submits a resume for review.
Parses resume document from a public file URL and returns extracted details.
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To start, connect both your MagicalAPI and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in MagicalAPI triggers actions in Coursera: Data Science Specialization (or vice versa).
Absolutely. You can customize how MagicalAPI 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 MagicalAPI 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 MagicalAPI 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.
MagicalAPI enables seamless integration for developers by providing scalable APIs for resume analysis and structured data extraction from public LinkedIn profiles and company pages.
Learn MoreMaster 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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