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Introduction to Optimization
The course introduces the use of mathematical models for managerial decision making
and covers how to formulate linear programming models for decision problems
where multiple decisions need to be made in the best possible way while
simultaneously satisfying a number of logical conditions (or constraints.)
Instructor: Dr. Cliff Ragsdale
August 26, 2011 to September 23, 2011
Natural Language Processing
This course is designed to give you an introduction to the algorithms, techniques and software used in natural language processing (NLP).
Instructor:
Dr. Nitin Indurkhya
September 02, 2011 to September 30, 2011
Forecasting
This course will teach you how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting.
Instructor:
Dr. Galit Shmueli
September 09, 2011 to October 07, 2011
Introduction to Data Mining
This course covers the two core paradigms that account for most business applications of data mining: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel.
Instructor:
Dr. Anthony Babinec
September 09, 2011 to October 07, 2011
National Income Statistics
This online course at statistics.com covers the essentials of National Income accounting.
Instructor:
Dr. Barbara Fraumeni
September 16, 2011 to October 07, 2011
Introduction to R - Data Handling
This course will provide an easy introduction to R and its use in organizing and exploring data. Once you've completed this course you'll be able to enter, save, retrieve, manipulate, summarize and display data using R.
Instructor:
Dr. Paul Murrell
September 16, 2011 to October 14, 2011
Introduction to Quantitative Risk Analysis
This course will cover the most important principles, techniques and tools used in modeling in Quantitative Risk Analysis.
Instructors:
Dr. Huybert Groenendaal and
Mr. Greg Nolder
September 23, 2011 to October 21, 2011
Advanced Optimization
This course covers a number of advanced topics in optimization. You will learn: 1) how to formulate and solve network flow problems, 2) how to model and solve optimization problems where some or all of the decision variables must be integers, 3) how to deal with multiple objectives in optimization problems, and 4) techniques for handling optimization problems where the objective function or constraints are not linear functions of the decision variables.
Instructor:
Dr. Cliff Ragsdale
September 30, 2011 to October 28, 2011
Data Mining: Unsupervised Techniques
This course covers key unsupervised learning techniques - association rules, principal components analysis, and clustering. The course will include an integration of supervised and unsupervised learning techniques.
Instructor:
Dr. Anthony Babinec
October 14, 2011 to November 11, 2011
Introduction to R - Statistical Analysis
This course covers how to use R for basic statistical procedures.
Instructor: Dr. John Verzani
October 14, 2011 to November 11, 2011
Statistical Analysis of Microarray Data with R
This course will acquaint you with the process of microarray data mining from beginning to end. You will learn how to how to preprocess the data, estimate gene expression patterns, cluster genes to detect interesting gene expression patterns, and classify experiments (subjects) based on gene expression patterns. Illustrations of the statistical issues involved at the various stages of the analysis will use real data sets from DNA microarray experiments.
Instructor:
Dr. Sudha Purohit
October 21, 2011 to November 18, 2011
Data Mining Mistakes and How to Avoid Them
The very nature of data mining makes it prone to error. This course reviews and illustrates the typical sources of error, and how to avoid them.
Instructor: Dr. John Elder IV
October 28, 2011 to November 25, 2011
Programming in R
The aim of the course is to give you the skills to work with a variety of data types and data sources in R. You'll also learn some techniques for programming "in-the-large", when you are trying to provide a suite of functions to flexibly solve a large class of problems.
Instructor:
Dr. Hadley Wickham
October 28, 2011 to November 25, 2011
Interactive Data Visualization
This course covers the principles of the visual display of data, both for presentation and analysis.
Instructors:
Dr. Galit Shmueli
and Dr. Catherine Plaisant
October 28, 2011 to November 25, 2011
Cluster Analysis
This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. Methods discussed include hierarchical clustering, k-means clustering, two-step clustering, and normal mixture models for continuous variables.
Instructor:
Dr. Anthony Babinec
November 04, 2011 to December 02, 2011
Graphics in R
The aim of this course is to teach you how to produce statistical plots of data using the R language and environment for statistical computing and graphics. The creation of standard plots such as scatterplots, bar plots, histograms, and boxplots will be covered and time will be spent on the underlying model used to produce plots in R so that you can extensively customize these plots.
Instructor: Dr. Paul Murrell
November 04, 2011 to December 02, 2011
Financial Risk Modeling
This course teaches participants how to model financial events that have uncertainties associated with them.
Instructors:
Dr. Huybert Groenendaal and
Mr. Greg Nolder
November 04, 2011 to December 02, 2011
Risk Simulation and Queuing
This course covers modeling technique making decisions in the presence of risk or uncertainty. Specific topics include risk analysis using Monte Carlo simulation for risk simulation, queuing theory for problems involving waiting lines, and decision trees for analyzing problems with multiple discrete decision alternatives.
Instructor: Dr. Cliff Ragsdale
November 18, 2011 to December 16, 2011
Data Mining: SAS Enterprise Miner Practicum
The purpose of this course is to take the knowledge learned in Introduction to Data Mining and Data Mining: Unsupervised Techniques and apply it using SAS Enterprise Miner.
Instructor: Dr. Robert A. Nisbet
November 25, 2011 to December 23, 2011
Programming in R - Advanced
This course will help you write better code, focused on the mantra of "do not repeat yourself". You will learn powerful new tools of abstraction, allowing you to solve a wider range of problems with fewer lines of code.
Instructor: Dr. Hadley Wickham
December 02, 2011 to January 06, 2012
Spatial Analysis Techniques in R
This course will teach users how to implement spatial statistical analysis procedures using R software.
Instructor: Dr. David Unwin
December 16, 2011 to January 20, 2012