[http://www.odum.unc.edu/content/image/UNC_ODUM_LOGO1.jpg]
"Big Data" Short Courses at UNC-Chapel Hill (June 23-27)
Sponsored by the National Consortium for Data Science<http://data2discovery.org> (NCDS), the Renaissance Computing Institute<http://www.renci.org> (RENCI), and the Odum Institute for Research in Social Science<http://www.odum.unc.edu>, the "Data Matters: Data Science Short Course Series" is a week-long series of classes for researchers, data analysts, and other individuals who wish to increase their skills in data studies and integrate data science methods into their research designs and skill sets. Scholars, analysts, and researchers from all disciplines and industries are welcome. Both one- and two-day courses will be offered; participants are welcome to register for one, two, or three classes. Classes will run from 9:30 a.m. to 4 p.m.
Fees: The early registration discount ends on May 12. For information on course fees, please click here<http://www.cvent.com/events/data-matters-data-science-summer-workshop-series/fees-accb286a7617465384f3abd5a45909e6.aspx>.
Descriptions: For course descriptions, please go to www.odum.unc.edu/datamatters<http://www.odum.unc.edu/datamatters>.
June 23-27
Friday Center for Continuing Education, UNC-Chapel Hill, NC.
Below are several "Data Matters" courses focusing on research using big data. For additional course descriptions, please visit www.odum.unc.edu/datamatters<http://www.odum.unc.edu/datamatters>.
Managing Big Data
June 23-24
Instructor: Arcot Rajesekar, School of Library and Information Science, UNC-Chapel Hill
Overview: We use Google to search and discover interesting topics, Facebook to get in touch with friends and family, LinkedIn to keep up with our professional contacts, Twitter to share our thoughts and to follow world events, and Amazon to buy books and stuff. But do we know how these large-scale, information-rich web-oriented services provide us with information within seconds? Do they use conventional databases such as relational databases? Do they store and retrieve their information in folders and files as we do on our desktops? Do they use traditional indexing schemes and information retrieval methods to discover relevant concepts? How can we automate the management of exponentially growing data, information, and knowledge? These are the emerging concepts that the next generation information managers needs to know -- cutting-edge technologies that play a vital role in dealing with our internetworked personal, social, and professional lives. These applications are highly data-intensive and management of these systems differs greatly from traditional relational database and file systems.
This course provides an introduction to concepts in NoSQL, a paradigm shift from traditional database management systems, and concepts in policy-based management of distributed data systems, an automation necessary for dealing with sharing data now and preserving it for the future. We will discuss examples from several enterprise and open source systems and provide hands-on experience in policy-based big data management.
If you have questions about this course, please contact [log in to unmask]<mailto:[log in to unmask]>. To register, go to www.odum.unc.edu/datamatters.
Large-scale Data Networks
June 25
Instructor: Manny Aparicio, Saffron Technology
This course will begin with a survey of cognitive computing to address the growing analytic challenges of large-scale data that tend to represent complex and diverse networks of people, places, and things. We will discuss new representations, such as graph databases and associative memories, and new statistical methods, such as lazy learning and algorithmic modeling, different from traditional databases and data modeling. Cross-industry applications will be highlighted, with exercises in data-to-knowledge transformations, including hands-on demonstrations of network analytics for sense-making and predictive/anticipatory analytics for decision making.
There are no pre-requisites, but familiarity with data representations and advanced data analysis is suggested. Suggested searches: cognitive computing, graph databases, semantic networks, link analysis, network analysis, entity network analytics, lazy learning, memory-based reasoning, associative memory base, algorithmic modeling, information distance, predictive analytics, anticipatory analytics.
If you have questions about this course, please contact [log in to unmask]<mailto:[log in to unmask]>. To register, go to www.odum.unc.edu/datamatters.
Hadoop for Huge Data Sets
June 25
Instructor: Erik Scott, Renaissance Computing Institute, UNC-Chapel Hill
Data sets continue to grow, seemingly without bound. Hadoop is a framework for dealing with these growing "monsters," which may include a mixture of complex and structured data. Created at Yahoo from work originally done by Google, Hadoop combines a fast filesystem with a surprisingly simple way to write massive parallel programs that run quickly. It is used in situations where researchers and information specialists would like to run analytics that are computationally extensive. Built on top of its core capabilities are the Pig and Hive database packages, tools which make it feasible to work with trillions of rows. This course will cover installation and use of Hadoop's filesystem, writing parallel programs (using the Map/Reduce paradigm), and the relational algebra and database capabilities of Pig and Hive. The session will include both lecture and in-class exercises.
If you have questions about this course, please contact [log in to unmask]<mailto:[log in to unmask]>. To register, go to www.odum.unc.edu/datamatters.
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Odum Institute
The University of North Carolina at Chapel Hill
Davis Library, 2nd Floor, CB# 3355
Chapel Hill, NC 27599-3355
www.odum.unc.edu<http://www.odum.unc.edu>
Telephone: 919.962.3061
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