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This course serves as an introduction to the data science principles required to tackle real-world, data-rich problems in business and academia, including:
Data acquisition, cleaning, and aggregation
Exploratory data analysis and visualization
Model creation and validation
Basic statistical and mathematical foundations for data science
January 24th to March 4th
Mondays and Thursday
6:30 - 9:30pm ET
Harold Li is currently a Data Scientist at Lyft. He is the instructor of the Intro to Data Science course.
He is a Princeton University graduate, Harold began his career as a strategist at Goldman Sachs, structuring various derivative strategies for corporate clients. After leaving the financial industry, he became a data science lead at Blue Apron, working cross-functionally on product launches, developing demand forecasting and LTV models, and devising methods to design desirable recipes for customers. At Lyft, he's currently working on initiatives that make passenger pickups as painless and convenient as possible. In his free time, you can find him posting on his data science blog, DataBucket, or playing squash and golf.
Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, and corporate programs based in Seattle, New York, Chicago, and San Francisco.
Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, and more. Students and 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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Metis Code of Conduct
Metis is dedicated to providing a harassment-free experience for everyone, regardless of gender identity, age, sexual orientation, disability, physical appearance, body size, race, or religion (or lack thereof).
We do not tolerate harassment of students, staff, or visitors in any form. Sexual language and imagery is not appropriate for any event including talks, workshops, parties, and other online media. Individuals and groups that do not abide by these rules will be asked to leave and, if necessary, prohibited from future events.
If you have any questions or you're made to feel uncomfortable by anyone on our campus or at one of our offsite events, please let one of the staff members know right away. The matter will be taken seriously and promptly addressed.