In business, data is only worth as much as the insights it provides, and insights rely completely on your ability to analyze and understand. Traditional artificial intelligence (AI) models require large annotated data sets leaving significant amounts of data untapped. This leaves valuable opportunities for your organization unrealized.
In the Unsupervised Machine Learning: Unlocking the Potential of Data online short course from the MIT Sloan School of Management and the MIT Schwarzman College of Computing, you’ll tap into your organization’s data to create new value. Over six weeks, you’ll explore the technical and strategic aspects of unsupervised machine learning (ML) within your business context. By learning the approaches, capabilities, limitations, and applications of ML, you’ll be able to deploy AI solutions tailored to your organization’s goals, and leverage the insights of your previously unutilized data.
Over six weeks, you’ll explore the business opportunities created by leveraging previously uncurated and unutilized data to train machine learning models. You’ll investigate how to build accurate AI models using representations, and how generative models can unlock the potential of your data. By exploring the landscape of pre-trained models, you’ll learn to create a strategy that ensures interpretability and causal inference in the deployment of ML in your organization. Finally, you’ll create a roadmap to ensure the models you’re employing are used in a responsible and maintenance-friendly manner.
