Data Intensive Summer School, June 30 – July 2, 2014
The Data Intensive Summer School focuses on the skills needed to manage, process and gain insight from large amounts of data. It is targeted at researchers from the physical, biological, economic and social sciences that are beginning to drown in data. We will cover the nuts and bolts of data intensive computing, common tools and software, predictive analytics algorithms, data management and visualization. Given the short duration of the summer school, the emphasis will be on providing a solid foundation that the attendees can use as a starting point for advanced topics of particular relevance to their work.
- Experience working in a Linux environment
- Familiarity with relational data base model
- Examples and assignments will most likely use R, MATLAB and Weka. We do not require experience in these languages or tools, but you should already have an understanding of basic programming concepts (loops, conditionals, functions, arrays, variables, scoping, etc.)
- Robert Sinkovits, San Diego Supercomputer Center
- Nuts and bolts of data intensive computing
- Computer hardware, storage devices and file systems
- Cloud storage
- Data compression
- Networking and data movement
- Data ManagementIntroduction to R programming
- Digital libraries and archives
- Data management plans
- Access control, integrity and provenance
- Introduction to Weka
- Predictive analyticsDealing with missing data
- Standard algorithms: k-mean clustering, decision trees, SVM
- Over-fitting and trusting results
- ETL (Extract, transfer and load)
- The ETL life cycle
- ETL tools – from scripts to commercial solutions
- Non-relational atabases
- Brief refresher on relational mode
- Survey of non-relational models and technologies
- Presentation of data for maximum insight
- R and ggplot package
Virtual Summer School courses are delivered simultaneously at multiple locations across the country using high-definition videoconferencing technology.
On June 26 I received a follow-up e-mail with notes from the instructors:
Preparing for the virtual summer school
Several of the instructors have requested that you preinstall software on your laptop. Given the large number of participants and the compressed schedule, we ask that you comply and do this before the start of the summer school.
R Studio (statistical programming language)
Follow “download RStudio Desktop”
WEKA (data mining software)
Follow “Download” link on left hand side of home page
Please download the Stable book 3rd ed. version
Prior knowledge of R is not required, but we do assume that you have some programming experience and familiarity with basic programming concepts (variables, arrays, loops, branching, etc.). You may find it helpful to acquaint yourself with basic R syntax ahead of time.
Reading the first two chapters of the following online introduction is recommended http://cran.r-project.org/doc/manuals/R-intro.html
A basic understanding of relational databases and SQL would also be useful. If you are unfamiliar with the SQL syntax, please consider the following tutorials
I already have R studio; I have never tried Weka. This is a little bit of added work for the summer, but it looks like a great opportunity to pick up some additional skills, or at least refresh those skills I’ve already acquired.