workshops
Events
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Sipping Big Data! A Tasty Conversation with ABInBev, the World’s #1 Brewer
OnlineThis half-day workshop will be hosted virtually in connection with the Newark site of Anheuser-Busch InBev.
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Big Data: The Future of Aviation
OnlineLearn how big data is transforming the aviation industry. Connect with aviation companies in South Jersey.
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Analytics, Data Science & Artificial Intelligence Workshop & Seminar Series @ Rutgers University: Intelligent Informatics @ Bloustein
Public Informatics for a Better Future: Textual Analytics with R and Social Media Data by Dr. Jim Samuel, Executive Director- Informatics, EJ Bloustein School of Planning & Public Policy, Rutgers, The State University of New Jersey
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Enabling Protein Structure Prediction with AI
Artificial Intelligence/Machine Learning (AI/ML) methods are being used for de novo protein structure prediction. In addition to expert lectures, this crash course will provide hands-on training on AlphaFold2 and RosettaFold. These methods made a big impact in the field of protein prediction by solving a 50-year-old grant challenge.
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Data Science Workshop Series: Introduction to Python
Recording available. Are you interested in learning data science and modern computational tools for your research? If so, come join our Data Science Workshop Series on topics including Python Programming, Machine Learning, Distributed Machine Learning for Big Data, and Deep Learning.
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Data Science Workshop: Python for Big Data
Recording available. In this workshop, we will go through some of these techniques including vectorization, parallelization, just in time compilation, and distributed task executions. We will do hands-on exercises to emphasize the following solutions.
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Data Science Workshop: Machine Learning with Python
In this workshop, after a brief overview on machine learning, we will focus on doing the hands-on training in applying ML models on various data types including image, text, and time series. We will work through the use cases of classification and regression problems and discuss where to apply supervised or unsupervised methods.