[gov3009-l] Fwd: Introducing Stat 221 -- Stat Computing and Visualization

Please see description of Stat 221 - a class on computing and visualization - below! -Konstantin ---------- Forwarded message ---------- From: Sergiy Nesterko &lt;nesterko(a)fas.harvard.edu <javascript:_e({}, 'cvml', &#x27;nesterko(a)fas.harvard.edu&#x27;);&gt;&gt; Date: Sat, Dec 15, 2012 at 3:52 PM Subject: Introducing Stat 221 -- Stat Computing and Visualization To: Hi! I'd like to introduce to you a class offered at Harvard in Spring 2013 on data analysis and visualization. Please check its description and forward this email to your awesome friends so that you can take the class together! * * *Statistical Computing and Visualization (Stat 221)* Do you want to learn how to analyze data efficiently and rigorously and how to make beautiful interactive visualizations<http://theory.info/harvardstat221#?v=network-of-individuals-at-risk-of-hiv>? Do you want to work on real life problems provided by course partners<http://theory.info/harvardstat221#partners> ? This course just might be what you need! Stat 221 is a graduate-level class aimed to equip PhD and Masters students (and motivated undergraduates) with practical distributed computing and visualization tools for data analysis. The class will feature 5 homeworks and a final project, and no exams. For the final project, students have an option to work in teams on important data-intensive problems provided by one of 15+ academic and corporate partners and collaborators<http://theory.info/harvardstat221#partners>, including: - Siemens - MIT - IBM - Starbucks - eBay - Deloitte - Caesar's Entertainment - many others Partners and collaborators will be in direct contact with the assigned student teams throughout the term. Main topics of the course: data analysis with Maximum Likelihood, EM, MCMC, Gibbs, HMC and variants, Bayesian modeling, and interactive visualization. Themes and tricks covered in class: fast R code, interactive visualization, Odyssey distributed computing, code aesthetics, MPI/rMPI, likelihood computation, algorithm tuning, model nonidentifiabilities, posterior predictive checks, frequentist model evaluation, parsimony in visualization, parsimony in modeling. Please see the attached syllabus<http://theory.info/media/files/stat221/Stat221syllabus.pdf> or visit the course website <http://theory.info/harvardstat221#> for more information. There is also an online presentation introducing the class<http://nesterko.com/talks/harvardstat221intro/> . If you are interested or have further questions, feel free to e-mail Sergiy Nesterko (the course instructor) at: nesterko@fas.harvard.edu<javascript:_e({}, 'cvml', &#x27;nesterko(a)fas.harvard.edu&#x27;);&gt; . *Pre-registration now open on *my.harvard.edu* (search for **Statistics 221* *)!* -- Konstantin Kashin Ph.D. Candidate in Government Harvard University Mobile: 978-844-0538 E-mail: kkashin(a)fas.harvard.edu Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashi…