Course Calendar

Year 2014

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April 2014

04FridayR Programming - Intermediate(4 weeks)
R for Statistical Analysis(4 weeks)
Generalized Linear Models(4 weeks)
Statistics 1 - Probability and Study Design(4 weeks)
Introductory Statistics for Credit(9 weeks)
Meta Analysis(4 weeks)
11FridayStatistics 2 – Inference and Association(4 weeks)
Discrete Choice Modeling and Conjoint Analysis(4 weeks)
Introduction to Quantitative Risk Analysis(4 weeks)
R Programming - Introduction 2(4 weeks)
Data Mining: Unsupervised Techniques(4 weeks)
18FridayStatistical Analysis of Microarray Data with R(4 weeks)
Survey of Statistics for Beginners(3 weeks)
25FridayAdvanced Logistic Regression(4 weeks)
Bayesian Regression Modeling via MCMC Techniques(4 weeks)
Interactive Data Visualization(4 weeks)
Applied Predictive Analytics, in partnership with CrowdANALYTIX(4 weeks)

May 2014

02FridayStatistics 1 - Probability and Study Design(4 weeks)
Graphics in R(4 weeks)
Introductory Statistics for Credit(9 weeks)
09FridayMixed and Hierarchical Linear Models(4 weeks)
Spatial Statistics with Geographic Information Systems(4 weeks)
Statistics 2 – Inference and Association(4 weeks)
R Programming - Introduction 1(4 weeks)
16FridayStatistics 3 – ANOVA and Regression(3 weeks)
Financial Risk Modeling(4 weeks)
Introduction to Structural Equation Modeling(4 weeks)
Regression Analysis(4 weeks)
Sample Size and Power Determination(4 weeks)
23FridayPrincipal Components and Factor Analysis(4 weeks)
Introduction to Bayesian Hierarchical and Multi-level Models(4 weeks)
Biostatistics in R: Clinical Trial Applications(4 weeks)
Modeling Count Data(4 weeks)
R Programming - Advanced(4 weeks)
30FridayPrediction & Tolerance Intervals; Measurement and Reliability(4 weeks)
Practical Rasch Measurement - Core Topics(4 weeks)
Advanced Analytics and Machine Learning with Hadoop(4 weeks)

June 2014

06FridayStatistics 2 – Inference and Association(4 weeks)
Text Mining(4 weeks)
Introduction to Statistics 1 AP: Inference for a Single Variable(3 weeks)
Calculus Review(3 weeks)
Statistics 1 - Probability and Study Design(4 weeks)
Introductory Statistics for Credit(9 weeks)
13FridayLogistic Regression(4 weeks)
R Programming - Introduction 2(4 weeks)
Introduction to Statistical Modeling(4 weeks)
20FridayIntroduction to Smoothing and P-spline Techniques using R(4 weeks)
Introduction to Statistical Issues in Clinical Trials(4 weeks)
Probability Distributions(4 weeks)
27FridayMatrix Algebra Review(4 weeks)
Data Mining - R(4 weeks)
Advanced Structural Equation Modeling(4 weeks)

July 2014

04FridayStatistics 1 - Probability and Study Design(4 weeks)
Practical Rasch Measurement - Further Topics(4 weeks)
Introduction to Resampling Methods(3 weeks)
Introduction to Bayesian Statistics(4 weeks)
Introductory Statistics for Credit(9 weeks)
11FridayStatistics 3 – ANOVA and Regression(3 weeks)
Introduction to Statistics 2 AP: Working with Bivariate Data(3 weeks)
Multivariate Statistics(3 weeks)
Survey Design and Sampling Procedures(4 weeks)
Statistics 2 – Inference and Association(4 weeks)
18FridayModeling Longitudinal and Panel Data(4 weeks)
Natural Language Processing(4 weeks)
Predictive Analytics 1 - Machine Learning Tools(4 weeks)
25FridayClinical Trials - Phamacokinetics and Bioequivalence(4 weeks)
R for Statistical Analysis(4 weeks)
Visualization in R with ggplot2(4 weeks)
Meta Analysis(4 weeks)

August 2014

01FridayStatistics 1 - Probability and Study Design(4 weeks)
Introductory Statistics for Credit(9 weeks)
R Programming - Introduction 1(4 weeks)
SQL and R - Introduction to Database Queries(4 weeks)
Maximum Likelihood Estimation(2 weeks)
08FridayStatistics 2 – Inference and Association(4 weeks)
Many-Facet Rasch Measurement(4 weeks)
Biostatistics 1(4 weeks)
Biostatistics for Credit(9 weeks)
15FridaySurvey Analysis(4 weeks)
Introduction to Python for Analytics(4 weeks)
Introduction to Social Network Analysis (SNA)(4 weeks)
22FridayIntroduction to Optimization(4 weeks)
Modeling in R(4 weeks)
Predictive Analytics 2 - Neural Nets and Regression(4 weeks)
Introduction to Item Response Theory (IRT)(4 weeks)
29FridayMeta Analysis 2(4 weeks)
Sentiment Analysis(4 weeks)
Introduction to Bayesian Computing and Techniques(4 weeks)
Political Analytics(4 weeks)

September 2014

05FridayStatistics 1 - Probability and Study Design(4 weeks)
Logistic Regression(4 weeks)
Statistics 2 – Inference and Association(4 weeks)
Introductory Statistics for Credit(9 weeks)
R Programming - Introduction 2(4 weeks)
12FridayStatistics 3 – ANOVA and Regression(3 weeks)
Rasch Applications, Part 1: How to Construct a Rasch Scale(6 weeks)
Introduction to Quantitative Risk Analysis(4 weeks)
Biostatistics 2(4 weeks)
Forecasting Analytics(4 weeks)
19FridaySurvival Analysis(4 weeks)
Bootstrap Methods(4 weeks)
Mapping in R(4 weeks)
26FridayAdvanced Optimization(4 weeks)
Bayesian Statistics in R(4 weeks)
Categorical Data Analysis(4 weeks)
R Programming - Intermediate(4 weeks)
Applied Predictive Analytics, in partnership with CrowdANALYTIX(4 weeks)

October 2014

03FridayMissing Data(4 weeks)
Regression Analysis(4 weeks)
R for Statistical Analysis(4 weeks)
Statistics 1 - Probability and Study Design(4 weeks)
Introductory Statistics for Credit(10 weeks)
10FridayStatistics 2 – Inference and Association(4 weeks)
Analysis of Survey Data from Complex Sample Designs(4 weeks)
Graphics in R(4 weeks)
Calculus Review(3 weeks)
17FridayData Mining: Unsupervised Techniques(4 weeks)
Practical Rasch Measurement - Core Topics(4 weeks)
24FridaySafety Monitoring Committees in Clinical Trials(4 weeks)
Bayesian Regression Modeling via MCMC Techniques(4 weeks)
31FridayCluster Analysis(4 weeks)
Modeling Count Data(4 weeks)
Introduction to Analytics using Hadoop(4 weeks)
Rasch Applications, Part 2: Clinical Assessment, Survey Research, and Educational Measurement(4 weeks)
Interactive Data Visualization(4 weeks)

November 2014

07FridayStatistics 1 - Probability and Study Design(4 weeks)
Categorical Data - Applied Modeling(4 weeks)
Spatial Statistics with Geographic Information Systems(4 weeks)
Introduction to Structural Equation Modeling(4 weeks)
Advanced Survival Analysis(4 weeks)
Introductory Statistics for Credit(10 weeks)
R Programming - Introduction 1(4 weeks)
14FridayStatistics 3 – ANOVA and Regression(3 weeks)
Epidemiologic Statistics(5 weeks)
Matrix Algebra Review(4 weeks)
Statistics 2 – Inference and Association(4 weeks)
21FridayRisk Simulation and Queuing(4 weeks)
Introduction to Bayesian Hierarchical and Multi-level Models(4 weeks)
Survey of Statistics for Beginners(3 weeks)
28FridayMeta Analysis(6 weeks)
Maximum Likelihood Estimation(1 weeks)

December 2014

05FridayStatistics 1 - Probability and Study Design(5 weeks)
Introductory Statistics for Credit(9 weeks)
12FridayStatistics 2 – Inference and Association(5 weeks)
Introduction to Statistical Issues in Clinical Trials(5 weeks)
Spatial Analysis Techniques in R(3 weeks)

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