Data Creation and Collection for AI via Crowdsourcing
Learn how to utilize crowdsourcing to collect diverse and representative datasets, implement effective active learning strategies, and maintain data quality for robust machine learning models.
Description for Data Creation and Collection for AI via Crowdsourcing
Crowdsourcing for Data Collection: Analyze the utilization of crowdsourcing to collect data for machine learning tasks.
Impact of Cognitive Biases: Describes the manner in which the quality of data is influenced by human factors, such as cognitive biases.
Active Learning in Crowdsourcing: This section covers the application of active learning techniques to generate crowdsourced training data.
Task Design with Quality Control: Illustrates the process of creating crowdsourcing tasks that incorporate mechanisms to guarantee the quality of the data.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On edX provided by DelftX
Duration: 4�5 hours per week approx 6 weeks
Schedule: Flexible
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