In the Mid-'70s in the hallowed halls of Bell Labs they developed Unix, C, and a lot of cool things. One of these was the S statistical programming language. Its modern implementations are S-plus and R.
R is an open source programming language for statistical computing, data analysis, and graphical visualization. While most commonly used within academia, in fields such as computational biology and applied statistics, it is rapidly gaining currency in commercial areas such as quantitative finance and business intelligence.
Among R's strengths as a language are its powerful built-in tools for inferential statistics, its compact modeling syntax, its data visualization capabilities, and its ease of connectivity with persistent data stores (from databases to flatfiles).
In addition, R is open source nature and extensible via add-on "packages" allowing it to keep up with the leading edge in academic research. For all its strengths, though, R has an admittedly steep learning curve; the first steps towards learning and using R can be challenging.
The Atlanta R Users Group is dedicated to bringing together area practitioners of R to exchange knowledge, inspire new users, and spur the adoption of R for innovative research and commercial applications.
They seem to have meetings by fits and starts, but check out their Meetup Page nonetheless.