Training AI with Humans
By External Provider
About this course
In the course "Training AI with Humans", you'll delve into the intersection of machine learning and human collaboration, exploring how to enhance AI performance through effective data annotation and crowdsourcing. You’ll gain a comprehensive understanding of machine learning principles and performance metrics while developing practical skills in using platforms like Amazon Mechanical Turk (AMT) for crowdsourced tasks. This unique approach combines theoretical knowledge with hands-on experience, allowing you to implement Inter-Annotator Agreement (IAA) techniques to ensure high-quality annotated data. By completing this course, you will be well-equipped to design and conduct impactful crowdsourcing studies, improving AI models in real-world applications such as healthcare and research. Whether you're looking to enhance your skills in machine learning, optimize data collection processes, or understand the ethical implications of crowdsourcing, this course offers invaluable insights and tools.
What you will learn
- Learn to construct and evaluate various machine learning classifiers and performance metrics.
- Master the calculation and implications of Inter-Annotator Agreement (IAA) for data consistency.
- Understand how to design and implement effective crowdsourcing tasks using Amazon Mechanical Turk.
- Analyze crowdsourced data to enhance machine learning models and understand ethical considerations in AI.