
When this happens...
New User
New Company
Company Updated
New Discoveries
New Messages
Automatically do this!
Enable Integrations or automations with these events of Harvestr and Coursera: Data Science Specialization
Triggers when a new user created.
Tiggers when a new company Cretaed.
Triggers when a new Company Update.
Tiggers when a new discoveries created.
Tiggera when a new message Cretaed.
Creates a new message in your inbox.
Create a new Company.
List all users.
List all companies
List all components
List all discoveries
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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your Harvestr and Coursera: Data Science Specialization accounts to viaSocket. Once connected, you can set up a workflow where an event in Harvestr triggers actions in Coursera: Data Science Specialization (or vice versa).
Absolutely. You can customize how Harvestr 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 Harvestr 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 Harvestr 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.
Harvestr is a product management tool that lets you centralize user feedback, prioritize features and communicate on your roadmap.
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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