This event will be Livestreamed here:https://livestream.com/metis/events/8565438
EVENTManaging Data Science projects is notoriously difficult. Going into a project it can be difficult or impossible to foresee data quality issues, which models will work well, & how much effort is necessary to ship a data product.
Leaning on a few years of leading data science engagements at startups & large companies, I've picked up a few tricks to keep data science projects on-time & meeting mission critical milestones, all while keeping data scientists happy. We'll touch on how data science projects differ from most software engineering projects, why its important to spend a bit more time planning them, & how to make sure your projects are a success.
BIOBrendan Herger enjoys bridging the gap between data science & engineering, to build & deploy data products. He is a Senior Data Scientist at Metis.
Brendan brings a unique combination of machine learning, deep learning, & software engineering skills. In his previous work at Capital One & startups, he has built authorization fraud, insider threat, & legal discovery automation platforms. In each of these cases he's lead a team of data scientists & data engineers to enable & elevate his client's business workflow (and capture some amazing data).
When he's not knee deep in a code base, Brendan can be found traveling, sharing his collection of Japanese teas, & playing board games with his partner in Seattle.
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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