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Big Data Course Plans at Purdue Ananth Iyer
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Big Data/Analytics Coursera course on Big Data by Bill Howe claims that Big Data involves issues of https://class.coursera.org/datasci-001/lecture/21 Volume (size of the data) Velocity (data processing speed vs receipt speed) Variety (diversity of data, formats, quality}
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At Purdue Big Data is being framed as a “certificate” that can be added to existing degree programs Run out of the graduate school as one of the “interdisciplinary certificates” A set of 25 faculty across all colleges from Statistics, Computer Science, EE, Agriculture (Remote Sensing), Management, Library Science, Genetics, Civil Engr, Forestry…. Plan to structure a core+applications
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Core Courses Proposed Fundamentals – Issues of scale, data structure, algorithms (data structures, complexity, classification, data visualization, geometry, graph theory) Machine Learning – understand machine learning, impact for large applications (data pipeline, neural nets, clustering, Bayesian learning) Data storage and organization – techniques for data storage and technologies (Twitter, Facebook data, HadoopDB, web services, workflow systems, cloud) Large Scale data collection, curation, modeling (physics, astronomy data, denoising, data cleaning, sampling, data reduction, parallel algorithms, streaming)
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Applications HD Sound files – use tools to separate spectrum and analyze biodiversity Video Streaming datasets – non-persistent data, extract data from flows, validate Twitter data – text analysis, context analysis Merge datasets to create customer focused information
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Online certificate Access to large datasets (Soundscapes, video repository of 1 million feeds, Twitter, Facebook, remote sensing) Select toolsets and host all software to do analysis Parallel machines to execute commands Data analysis and project
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