Michael Li and Rich Ott offer a nontechnical overview of AI and data science. Learn common techniques, how to apply them in your organization, and common pitfalls to avoid. You’ll pick up the language and develop a framework to be able to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making.
Introduction to AI and data science
Algorithms and techniques
Industry use cases
AI within the organization
Common pitfalls and fallacies in AI and data science
Michael Li is the founder of the Data Incubator, an elite fellowship program that trains and places data scientists and quants with advanced degrees (PhD or masters) into industry roles. Previously, Michael was a data science lead with Foursquare and with Andreessen Horowitz. He holds PhD in math from Princeton University.
Richard Ott is a data scientist in residence at the Data Incubator, where he gets to combine his interest in data with his love of teaching. Previously, he was a data scientist and software engineer at Verizon. Rich holds a PhD in particle physics from the Massachusetts Institute of Technology, which he followed with postdoctoral research at the University of California, Davis.
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