Slideshow 9 summer programs to boost analytics skills

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  • June 14 2016, 7:34am EDT
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9 Summer Programs to Boost Your Big Data Skills

Looking to sharpen your data management and data analytics skills this summer? Here are nine programs to help you sort out where big data trends are heading and how they will impact your organization and your career.

Data Matters: Data Science Short Courses

June 20 to 24: The Howard W. Odum Institute for Research in Social Science/University of North Carolina at Chapel Hill Chapel Hill, NC.
Sponsored by the National Consortium for Data Science (NCDS), the Renaissance Computing Institute (RENCI), and the Odum Institute for Research in Social Science, the "Data Matters: Data Science Summer Workshop 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. For more information, click here.

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Big Data on the Great Plains: North Central Section MAA Summer Seminar 2016

June 22 to July 24: Summer seminar, The Mathematics Association of America/South Dakota State University Brookings, SD.
Topics include workshops on Getting the Data; Big Data and Optimization; Statistical Methods using R; Big Data in Genomics; Big Data in Precision Agriculture; and Developer apps. On June 21, there is an optional one-day workshop on programming with R. For more information go here.

Data Analysis Summer 2016

June 22 to June 29: Montgomery College Rockville, MD.
Topics covered in this one-week intensive program include big data and databases; business applications; cybersecurity; data analysis; digital graphics; social media; and more. More information is here.

Emerging Technologies in Big Data

June 29 to August 31: University of Washington Seattle, WA.
Topics include: Designing for end-user experiences and testing client usage; System integration; Lambda architecture; System performance; Scalable distributed systems; Security; and case studies involving current technology trends. More information can be found here.

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26th Annual PCMI Summer Session: The Mathematics of Data

June 30 to July 20: The Institute for Advanced Study (IAS)/Park City Mathematics Institute (PCMI) Princeton, NJ.
The Institute for Advanced Study/Park City Mathematics Institute is designed for mathematics educators at the secondary and post-secondary level, as well as mathematics researchers and students at the post-secondary level. More information can be found here.

Big Data in the Big Apple

July 5 to August 12: Columbia University New York.
Data mining, artificial intelligence, and machine learning are just some of the topics that will be covered in this summer program, which promises attendees a number of data-intensive offerings by several university departments, but all “with a New York twist.” For more information, click here.

Summer Institute in Statistics for Big Data

July 11 to July 29: The Center for Sensorimotor Neural Engineering/University of Washington Seattle, WA.
The Institute consists of a series of two-and-a-half day workshops (modules) designed to introduce biologists, quantitative scientists, and statisticians to modern statistical techniques for the analysis of biological big data. The format will involve formal lectures, computing labs, and hands-on case studies. More information can be found here.

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2016 Big Data Analytics Summer Experience

July 11 to July 29: University of Missouri Columbia.
This program will introduce several key Big Data processing and analytics technologies, teach practical skills and practices and offer hands-on experiences. Topics covered include: Introduction to Big Data and Big Data technologies; Hadoop; MapReduce; Querying Big Data with Hive; and Mining Big Data with Spark MLlib. More information can be found here.

2nd Summer Institute in Statistics for Big Data

July 11 to July 29: University of Washington Seattle, WA.
With a heavy focus on healthcare data, this three week program includes sessions on Big Data Wrangling; Visualization of Biomedical Big Data; Reproducible Research for Biomedical Big Data; Supervised Methods for Statistical Machine Learning; and Unsupervised Methods for Statistical Machine Learning. More information can be found here.