This event will be Livestreamed here:
Data Science is a field with immense breadth & depth. As our toolkit grows & we learn how to chain models & pipelines together, there's no limit to the time & complexity we can devote to over-engineering a solution. In my role as a data science instructor at Metis, & during my tenure at Microsoft before that, I've observed time & again that many data scientists seem to be much better at learning algorithms & software libraries than they are at identifying good business cases to solve, & designing workflows that will enable them to work productively from start to finish.
In this workshop I share a user-focused design approach to building an end-to-end minimum viable product for any data science project. By asking & answering the right questions at the start of any new project, we can set a course that points to clear choices for the design decisions we face along the way. I teach this in the context of building a music genre classification model that can be used to generate playlists from text descriptions.
Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, & corporate programs based in Seattle, New York, Chicago, & San Francisco.
Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, & more. Students & alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science.
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