Questions? Read our FAQs
Questions? Read our FAQs
Overview: Regardless of your job function and industry, it is becoming increasingly crucial to be able to make better decisions based on data. Data Science allows you to understand, draw insights from, and leverage your data more effectively.
What You’ll Take Away: Practical tips on moving into a data-related career and how to progress in the field.
Why It Matters: If you're considering a career change into data science, find out first-hand from industry professionals what the day-to-day looks like and what to expect from a career in data.
Arezu Moussavi is a PhD student graduating in summer 2016. She pursued machine learning during her PhD program and focused on deep learning using autoencoders. She always eager to learn and experience new topics in machine learning and apply her knowledge to the real-world problems. As a winner of the best teaching award from the engineering department during working on campus, she believes that teaching is a mutual learning process and enjoys teaching.
University of Washington eScience Institute
Bernease Herman is a data scientist and researcher at the University of Washington eScience Institute. Her research focuses on interpretable machine learning with work in fairness, accountability, and transparency. In her work, she collaborates with academic researchers, startups, and non-profits with applications of machine learning across domains. She's worked on problems from data collection and analysis strategies in autonomous marine vehicles to predicting inequity in Seattle urban data.
Before joining UW eScience, Bernease was a Software Development Engineer at Amazon, where she collaborated with operations research scientists and statisticians to optimize statistical inventory models to Amazon’s Inventory Planning and Control system. Previous to Amazon, Bernease worked on derivatives pricing and predictive modeling at the research arm of Morgan Stanley. Bernease earned her BS in Mathematics and Statistics from the University of Michigan.
She spends her time Olympic weightlifting, rowing, as well as hunting down simplified explanations and analogies for new concepts.
We understand that, sometimes, plans change. If you can no longer make it to a class or workshop, please email us at least 7 days before the scheduled event date. No refunds will be given to cancellations made within a week of the class or workshop.
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