Sponsored Announcement by SlideRule. Classes start January 5, 2015.
- Probability and statistics: Probability & combinatorics, random variables & distributions, descriptive statistics, dependent & independent events, regression and inferential statistics. (16 hours)
- R Basics: Installing R and RStudio, shortcuts, common commands, syntax quirks and basic visualization with the ggplot2 package. (4 hours)
- Exploratory Data Analysis: EDA vs classical & Bayesian approaches, histograms, frequency polygons, box-plots, quartiles, scatter plots, heat maps etc. (20 hours)
- Data Wrangling: The split-apply-combine paradigm, R based tools and packages for data wrangling - reshape2, plyr, dplyr etc. (4 hours)
- Analytics Techniques: Learn how to apply analytics to real-world applications from examples including Moneyball, eHarmony, Twitter, IBM Watson, and Netflix. Linear & logistic regression, trees, clustering and text analytics. (45+ hours)
- Capstone Project: Bring it all together with the Capstone project! Pick a data set in your area of interest, tidy it up, explore & summarize it to form an intuition and then use formal methods to build a model and uncover insights! (10+ hours)