Online Courses in Predictive Analytics, Machine Learning, Data Science from Statistics.com
Many interesting online courses covering Decision Trees, Machine Learning Tools, Python for Analytics, Social Network Analysis, Hadoop, Forecasting, Data Visualization, and more, from Statistics.com.
Here is a schedule of upcoming courses from Statistics.com.
Jan 17 

Decision Trees and RuleBased Segmentation. (4 weeks, online) This course teaches you data mining classification/rule generation for prediction (classification and regression trees) and for recommender systems (association rules). 
Jan 31–
July 18

Predictive Analytics 1  Machine Learning Tools. (4 weeks, online) Introduces the concept of predictive modeling and use of holdout samples and various metrics for model assessment; covers Knearestneighbor (KNN), Naive Bayes, CART, ensembles. 
Feb 14 –
Aug 15 

Introduction to Python for Analytics. (4 weeks, online) An introduction for those with some programming or command line scripting familiarity. Data structures, strings, data handling, Pandas, merging, joining, visualization with matplotlib. 
Feb 21 
Aug 129 
SQL and R  Introduction to Database Queries. (4 weeks, online) An introduction to using SQL to extract data from relational databases, and then work with it in R. Database structure, SQL functions for selection, counting and arithmetic, subqueries, joins, and then work in R & Plyr. 
Feb 28 –
Aug 15 

Introduction to Social Network Analysis (SNA). (4 weeks, online) Basic terms and metrics, constructing plots, measuring tie strength and trust, content analysis, propagation, sampling and analysis, illustrations of applications. Taught Jen Golbeck, Director of the HumanComputer Interaction Lab at the University of Maryland, College Park. 
Mar 7 –
Aug 22 –

Predictive Analytics 2  Neural Nets and Regression. (4 weeks, online) Logistic and linear regression, discriminant analysis, neural networks. Assumes familiarity with the modeling process and model assessment taught in Predictive Analytics 1. 
Mar 7 –

Political Analytics. (4 weeks, online) Predictive modeling applied to political campaigns  "microtargeting." The instructor, Ken Strasma, directed targeting for the Obama campaign. 
Mar 28 
Oct 31

Introduction to Analytics using Hadoop. (4 weeks, online) Handson: set up your own Hadoop development environment. HDFS, MapReduce, data flow, functional programming with Mappers and Reducers, Hadoop streaming. 
Mar 28 
Sep 12 

Forecasting Analytics. (4 weeks, online) Leach how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting. Regression models, Moving Average, exponential smoothing, Autoregressive models. Taught by Galit Shmueli, author of numerous books in data mining and analytics. 
Apr 25 
Oct 24 

Interactive Data Visualization. (4 weeks, online) The focus is not on presentation, but on exploration and analysis. Time series, scatterplots, trellis plots, parallel coordinate plots, treemaps. Choose different variables, different plots, and different filters all on the same dataset to gain knowledge. 
Jun 6 

Text Mining. (4 weeks, online) This course extends data mining's standard predictive methods to unstructured text. Tokenizations, dictionary creation, vector generation, feature generation. 
Jun 28

Data Mining in R. (4 weeks, online) This course uses cases to teach you how to use R (with which you should be familiar) for predictive modeling. Taught by Luis Torgo, author of "Data Mining with R." 
Jul 19

Natural Language Processing. (4 weeks, online) This course teaches the concepts and techniques of NLP  text preprocessing, corpus creation, lexical analysis, tagging, parsing, semantic analysis. Taught by author Nitin Indurkhya, who first coined the term Big Data in 1998. 
Aug 29

Sentiment Analysis. (3 weeks, online) Sentiment Analysis refers to the process of identifying, extracting and classifying opinions in text segments (used in CRM, online advertising and brand analysis). Taught by author Nitin Indurkhya, who first coined the term Big Data in 1998. 
Sep 26 

Bayesian Statistics in R (4 weeks, online) Learn how to run Bayesian regression models in R  linear, linear regression, poisson, logit and negative binomial regression, and ordinal regression. Use JAGS and RINLA. Taught by Peter Congdon, author of several books on Bayesian computing. 
Oct 10 

Data Mining: Unsupervised Techniques (4 weeks, online) This course covers Principal Components Analysis, hierarchical and kmeans clustering, association rules, and the integration of unsupervised methods into predictive modeling. 
Oct 31 

Cluster Analysis (4 weeks, online) This course is an indepth look at hierarchical clustering (divisive vs. agglomerative), kmeans clustering, Normalmixture models, and twostep clustering. Taught by Anthony Babinec, president of AB Analytics. 
Nov 21

Risk Simulation and Queuing. (4 weeks, online) This course covers simulation to analyze risk, poisson arrival rate simulation, queuing, decision analysis (decision tree, payoff matrix, expected value of information, tornado charts. Taught by Cliff Ragsdale, author of "Spreadsheet Modeling and Decision Analysis: A Practical Introduction  Management Science" 