# What do you want to learn today?

## Courses

In this course you will learn how to examine data with the goal of detecting anomalies or abnormal instances.

**Topic:**Data Science, Machine Learning |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Oct 16, 2020, Oct 15, 2021

This course will teach you how to specify and run Bayesian modeling procedures using regression models for continuous, count and categorical data Using R and the associated R package JAGS.

**Topic:**Statistics, Bayesian |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**Mar 20, 2020, Sep 18, 2020

This course teaches the principal statistical concepts used in medical and health sciences. Basic concepts common to all statistical analysis and of specific importance in medicine and health are covered in detail.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: ACE, CEU

**Class Start Dates:**Jan 3, 2020, Jul 31, 2020

This course teaches you clinical trial designs including randomized controlled trials, ROC curves, CI and tests for relative risk and odds ratio, and an introduction to survival analysis.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: ACE, CEU

**Class Start Dates:**Feb 7, 2020, Aug 28, 2020

Biostatistics for Credit reviews the procedures covered in the introductory courses Biostatistics 1 and Biostatistics 2, and covers in more detail the principal statistical concepts used in medical and health sciences.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: ACE, CEU

**Class Start Dates:**Jan 3, 2020, Jul 31, 2020

This is a one-week preview of the Biostatistics course and covers the topics of medical uncertainty and probability, sensitivity-specificity and predictive values of medical tests.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate

**Class Start Dates:**Jul 24, 2020

This course will teach you the basic theory and application of the bootstrap family of procedures with the emphasis on applications.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**Sep 11, 2020, Sep 10, 2021

This course will teach you the analysis of contingency table data. Topics include tests for independence, comparing proportions as well as chi-square, exact methods, and treatment of ordered data. Both 2-way and 3-way tables are covered.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: ACE, CEU

**Class Start Dates:**Apr 3, 2020, Oct 2, 2020

This course will teach you the statistical measurement and analysis methods relevant to the study of pharmacokinetics, dose-response modeling, and bioequivalence. The course provides practical work with actual/simulated clinical trial data.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Jul 17, 2020

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.

**Topic:**Statistics, Analytics, Marketing Analytics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**May 29, 2020

An overview of visualization in Python

**Topic:**Analytics, Experimental Design |

**Skill**: Intermediate |

**Credit Options**: CEU

In this course you will work through a customer analytics project from beginning to end, using R.

**Topic:**Analytics, Marketing Analytics |

**Skill**: Introductory |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**May 15, 2020, Nov 13, 2020, May 14, 2021, Nov 12, 2021

This course will introduce you to the essential techniques of text mining as the extension of data mining’s standard predictive methods to unstructured text.

**Topic:**Data Science, Machine Learning |

**Skill**: Intermediate |

**Credit Options**: ACE, CEU

**Class Start Dates:**Nov 6, 2020

This course will teach you how to design studies to produce statistically valid conclusions. Topics covered in the course include: overview of validity and bias, selection bias, information bias, and confounding bias.

**Topic:**Statistics, Biostatistics |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Feb 14, 2020

This course will teach you to design appropriate conjoint and choice studies using surveys, panels, designed experiments, be able to analyze and interpret the resulting data.

**Topic:**Analytics, Marketing Analytics |

**Skill**: Intermediate, Advanced |

**Credit Options**: CAP, CEU

**Class Start Dates:**Aug 28, 2020

This course will teach you sampling methods and analyses used to study of the density and abundance of animals and plants and other important biological variables.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: CEU

This course will teach you the underlying concepts and methods of epidemiologic statistics: study designs, and measures of disease frequency and treatment effect.

**Topic:**Statistics, Biostatistics |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Nov 6, 2020

This course will teach you how to model financial events that have uncertainties associated with financial events.

**Topic:**Analytics, Operations Research |

**Skill**: Intermediate, Advanced |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jun 12, 2020

This course will teach you how to choose an appropriate time series model: fit the model, conduct diagnostics, and use the model for forecasting.

**Topic:**Analytics, Prediction/Forecasting |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 13, 2020, Jul 10, 2020, Nov 13, 2020, Mar 12, 2021, Jul 9, 2021, Nov 12, 2021

This course will explain the theory of generalized linear models (GLM), outline the algorithms used for GLM estimation, and explain how to determine which algorithm to use for a given data analysis.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**Apr 10, 2020

This course will teach you the statistical display and analysis methods used in monitoring clinical trials for safety, as well as the biases and pitfalls inherent in safety review.

**Topic:**Statistics, Biostatistics |

**Skill**: Introductory, Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Apr 24, 2020, Apr 24, 2021

This course will teach you a number of advanced topics in optimization: how to formulate and solve network flow problems; how to model and solve optimization problems; how to deal with multiple objectives in optimization problems, and techniques for handling optimization problems.

**Topic:**Analytics, Operations Research |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Sep 18, 2020

This course will teach you the principles of the visual display of data both for presentation and analysis data.

**Topic:**Analytics, Data Exploration |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 13, 2020, Jul 10, 2020, Nov 13, 2020, Mar 12, 2021, Jul 9, 2021, Nov 12, 2021

This course will teach you how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS software.

**Topic:**Statistics, Bayesian |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**Feb 21, 2020, Aug 21, 2020

This course will teach you how to extend the Bayesian modeling framework to cover hierarchical models and to add flexibility to standard Bayesian modeling problems.

**Topic:**Statistics, Bayesian |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**May 15, 2020

This course will teach you the basic ideas of Bayesian Statistics: how to perform Bayesian analysis for a binomial proportion, a normal mean, the difference between normal means, the difference between proportions, and for a simple linear regression model.

**Topic:**Statistics, Bayesian |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**Jan 17, 2020, Jul 3, 2020

This course will teach you the application of DOE rather than statistical theory, and teaches full and fractional factorial designs, Plackett-Burman, Box-Behnken, Box-Wilson and Taguchi designs.

**Topic:**Analytics, Experimental Design |

**Skill**: Introductory, Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**Mar 13, 2020

This course will teach you the statistical basis for analyzing multiple-choice survey or test data – item response theory (IRT).

**Topic:**Statistics, Tests & Surveys |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Feb 14, 2020

In this course, students learn how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using R and rstan.

**Topic:**Statistics, Bayesian |

**Skill**: Intermediate, Advanced |

**Credit Options**: CAP, CEU

**Class Start Dates:**Apr 17, 2020, Apr 16, 2021, Apr 15, 2022

This course will teach you a mix of quantitative and qualitative methods for describing, measuring, and analyzing social networks.

**Topic:**Analytics, Data Exploration |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Feb 21, 2020

This course will introduce you to the basics of programming in Python on either Windows or Mac platform.

**Topic:**Data Science, Using Python |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Jan 10, 2020, May 15, 2020, Sep 11, 2020, Jan 15, 2021

The course introduces the basic concepts and methods of resampling methods including bootstrap procedures and permutation with little or no complex theory or confusing notation.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Introductory, Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Mar 6, 2020

This course will teach you the basic statistical principles in the design and analysis of randomized controlled trials.

**Topic:**Statistics, Biostatistics |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Dec 7, 2019, Jun 12, 2020, Dec 4, 2020

This is a one-week preview of the Statistics 1 – Probability and Study Design course. No background in statistics is necessary.

**Topic:**Statistics, Introductory Statistics |

**Skill**: Introductory

This course will teach you the fundamental concepts and theory of Structural Equation Modeling, including model specification, model identification, model estimation, model testing, and model modification.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**May 15, 2020, Oct 30, 2020

This course will teach you the equivalent of a semester course in introductory statistics.

**Topic:**Statistics, Introductory Statistics |

**Skill**: Introductory |

**Credit Options**: ACE, CEU

This course will teach you logistic regression ordinary least squares (OLS) methods to model data with binary outcomes rather than directly estimating the value of the outcome, logistic regression allows you to estimate the probability of a success or failure.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**Jan 10, 2020, Jul 17, 2020

This course focuses is on learning the Weka tool in contrast to other courses where the focus is on a more detailed study of the data mining methods.

**Topic:**Data Science, Machine Learning |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Feb 7, 2020, Feb 12, 2021

This course will teach you the analysis and interpretation of judge-intermediated ratings, like essay grading, Olympic ice-skating, therapist ratings of patient behavior, etc.

**Topic:**Statistics, Tests & Surveys |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**Aug 7, 2020

This course will teach you how spatial data may be visualized in R and provides a review of a number of other diverse methods for visually representing geographical information in R.

**Topic:**Analytics, Data Exploration |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**May 1, 2020, Nov 20, 2020

This course will teach you the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 27, 2020, Aug 14, 2020

This course will teach you the derivation of maximum likelihood estimates and their properties.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Apr 17, 2020

This course will explain meta analysis and the methods that are used to assess multiple statistical studies on the same subject and draw conclusions.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Jul 17, 2020, Nov 6, 2020

This course will teach you advanced issues in meta-analysis and the statistical analyses that are used to synthesize summary data from a series of studies.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Aug 21, 2020, Aug 20, 2021

The course covers the fundamentals of the fixed and random effects models for meta-analysis, the assessment of heterogeneity, and evaluating bias.

**Topic:**Statistics, Biostatistics |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Oct 16, 2020

This course will teach you the basic theory of linear and non-linear mixed effects models, hierarchical linear models, algorithms used for estimation, primarily for models involving normally distributed errors, and examples of data analysis.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**Apr 24, 2020

This course will teach you regression models for count data, models with a response or dependent variable data in the form of a count or rate, Poisson regression, the foundation for modeling counts, and extensions and modifications to the basic model.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CAP, CEU

**Class Start Dates:**Oct 23, 2020

This course will show you how to use R to create statistical models and use them to analyze data.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CAP, CEU

**Class Start Dates:**Jun 19, 2020

This course will teach you key multivariate procedures such as multivariate analysis of variance (MANOVA), principal components, factor analysis, and classification.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**Jan 31, 2020

This course will teach you the algorithms, techniques and software used in natural language processing (NLP).

**Topic:**Data Science, Text Mining |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Feb 28, 2020

This course will introduce you to natural language processing (NLP) processes into your projects and software applications.

**Topic:**Data Science, Text Mining |

**Skill**: Intermediate, Advanced |

**Credit Options**: CAP, CEU

**Class Start Dates:**Sep 11, 2020

This course will teach you the use of mathematical models for managerial decision making and covers how to formulate linear programming models where multiple decisions need made while satisfying a number of conditions or constraints.

**Topic:**Data Science, Operations Research |

**Skill**: Introductory |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 10, 2020, Jul 17, 2020

This course will teach you how to apply predictive modeling methods to identify persuadable individuals and to target voters in political campaigns.

**Topic:**Analytics, Prediction/Forecasting |

**Skill**: Intermediate |

**Credit Options**: ACE, CEU

**Class Start Dates:**Feb 28, 2020, Aug 21, 2020

A predictive modeling practicum for the predictive analytices course program.

**Topic:**Analytics, Machine Learning |

**Skill**: Introductory, Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Feb 28, 2020

This course introduces to the basic concepts in predictive analytics to visualize and explore data that account for most business applications of predictive modeling: classification and prediction.

**Topic:**Analytics, Prediction/Forecasting |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 10, 2020, May 15, 2020, Sep 11, 2020, Jan 15, 2021

This course introduces to the basic concepts in predictive analytics, with a focus on Python, to visualize and explore data that account for most business applications of predictive modeling: classification and prediction.

**Topic:**Data Science, Analytics, Prediction/Forecasting, Using Python |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 10, 2020, May 15, 2020, Sep 11, 2020

This course introduces to the basic concepts in predictive analytics, with a focus on R, to visualize and explore data that account for most business applications of predictive modeling: classification and prediction.

**Topic:**Data Science, Analytics, Prediction/Forecasting, Using R |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 10, 2020, May 15, 2020, Sep 11, 2020

As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics to visualize and explore predictive modeling.

**Topic:**Analytics, Prediction/Forecasting |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Feb 21, 2020, Jun 26, 2020, Oct 23, 2020

As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics, with a focus on Python, to visualize and explore predictive modeling.

**Topic:**Data Science, Analytics, Prediction/Forecasting, Using Python |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Feb 21, 2020, Jun 26, 2020, Oct 23, 2020

As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics, with a focus on R, to visualize and explore predictive modeling.

**Topic:**Data Science, Analytics, Prediction/Forecasting, Using R |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Feb 21, 2020, Jun 26, 2020, Oct 23, 2020

This course will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.

**Topic:**Analytics, Prediction/Forecasting |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 3, 2020, Apr 10, 2020, Jul 31, 2020

This course, with a focus on Python, will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.

**Topic:**Data Science, Analytics, Prediction/Forecasting, Using Python |

**Skill**: Introductory, Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Jan 3, 2020, Apr 10, 2020, Jul 31, 2020

This course, with a focus on R, will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.

**Topic:**Data Science, Analytics, Prediction/Forecasting, Using R |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 3, 2020, Apr 10, 2020, Jul 31, 2020

This is a one-week preview of the Predictive Analytics 1 – Machine Learning Tools course and introduces the basic concepts in predictive analytics as the most prevalent form of data mining.

**Topic:**Analytics, Prediction/Forecasting |

**Skill**: Introductory

**Class Start Dates:**Dec 13, 2019

In this course, you will learn how to make decisions in building a factor analysis model – including what model to use, the number of factors to retain, and the rotation method to use.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**May 15, 2020

This course will teach you the basic Python skills and data structures – how to load data from different sources and aggregate it, and how to analyze and visualize it to create high-quality products.

**Topic:**Analytics, Using Python |

**Skill**: Introductory |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 13, 2020, Jul 10, 2020, Nov 13, 2020, Mar 12, 2021

This course will teach you how to use R for basic statistical procedures.

**Topic:**Data Science |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

This course will teach you key concepts for writing advanced R code, emphasizing the design of functional and efficient code. After completing the course, students should be able to read, understand, modify, and create complex functions to perform a variety of tasks.

**Topic:**Data Science, Using R |

**Skill**: Advanced |

**Credit Options**: CAP, CEU

**Class Start Dates:**Jan 3, 2020, Jun 19, 2020, Jan 1, 2021

This course will teach experienced data analysts a systematic overview of R as a programming language, emphasizing good programming practices and the development of clear, concise code. After completing the course, students should be able to manipulate data programmatically using R functions of their own design.

**Topic:**Data Science, Using R |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 27, 2020, Sep 18, 2020, Mar 26, 2021

This course provides an easy introduction to programming in R.

**Topic:**Data Science, Using R |

**Skill**: Introductory |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 10, 2020, May 15, 2020, Sep 11, 2020

This course is a continuation of the introduction to R programming.

**Topic:**Data Science, Using R |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 13, 2020, Jul 17, 2020, Nov 13, 2020, Mar 12, 2021

This course will teach you how Rasch analysis constructs linear measures from scored observations. You will learn the practical aspects of data setup, analysis, output interpretation, fit analysis, differential item functioning, dimensionality and reporting.

**Topic:**Statistics, Tests & Surveys |

**Skill**: Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Jan 24, 2020, May 22, 2020, Oct 9, 2020

This course will teach you Rasch theory and its application in the Winsteps software begun in Practical Rasch Measurement-Core Topics. This course introduces exciting new topics and delves into earlier topics more deeply.

**Topic:**Statistics, Tests & Surveys |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**Jun 26, 2020, Jun 25, 2021

This course will teach you how multiple linear regression models are derived, assumptions in the models, how to test whether data meets assumptions, and develop strategies for building and understanding useful models.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 17, 2020, May 8, 2020, Oct 2, 2020

This course will teach you modeling technique making decisions in the presence of risk or uncertainty, including risk analysis using Monte Carlo simulation, queuing theory for problems involving waiting lines, and decision trees for analyzing problems with multiple discrete decision alternatives.

**Topic:**Analytics, Operations Research |

**Skill**: Introductory |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**May 1, 2020, Nov 13, 2020

This course will teach you how to make sample size determinations for various statistical tests and for confidence intervals, as needed for experimental studies such as comparison studies, as well as for other types of experiments.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Introductory, Intermediate |

**Credit Options**: CEU

**Class Start Dates:**Apr 10, 2020, Oct 30, 2020

This course will teach you spatial statistical analysis methods to address problems in which spatial location. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.

**Topic:**Statistics, Analytics, Data Exploration, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jun 5, 2020, Oct 23, 2020

This course will teach you how to extract data from a relational database using SQL and merge data into a single file in R so that you can perform statistical operations.

**Topic:**Data Science, SQL |

**Skill**: Introductory, Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 13, 2020, Jul 31, 2020, Mar 12, 2021, Jul 30, 2021

This course, the first of a three-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics.

**Topic:**Statistics, Introductory Statistics |

**Skill**: Introductory |

**Credit Options**: ACE, CAP, CEU

This course, the second of a three-course sequence, will teach you the use of inference and association through a series of practical applications, based on the resampling/simulation approach, and how to test hypotheses, compute confidence intervals regarding proportions or means, computer correlations, and use of simple linear regressions.

**Topic:**Statistics, Introductory Statistics |

**Skill**: Introductory |

**Credit Options**: ACE, CEU

**Class Start Dates:**Dec 6, 2019

This course, the third of a three-course sequence, provides ananalysis of variance (ANOVA) and multiple linear regression through a series of practical applications.

**Topic:**Statistics, Introductory Statistics |

**Skill**: Introductory, Intermediate |

**Credit Options**: CEU

This course will teach you how to implement structural equation models (SEM) using R.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate, Advanced |

**Credit Options**: CEU

**Class Start Dates:**May 15, 2020

This course will teach you how to analyze data gathered in surveys.

**Topic:**Statistics, Tests & Surveys |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Sep 11, 2020

**Topic:**Statistics, Tests & Surveys |

**Skill**: Introductory |

**Credit Options**: CEU

**Class Start Dates:**Mar 20, 2020, Aug 7, 2020

This course will teach you the various methods used for modeling and evaluating survival data or time-to event data.

**Topic:**Statistics, Statistical Modeling |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Mar 6, 2020, Sep 11, 2020

This course will teach you the essential techniques of text mining, understood here as the extension of data mining’s standard predictive methods to unstructured text.

**Topic:**Data Science, Text Mining |

**Skill**: Intermediate |

**Credit Options**: ACE, CAP, CEU

**Class Start Dates:**Jan 31, 2020

This course will teach you ggplot as an implementation of the grammar of graphics in R. ggplot combines the advantages of base and lattice graphics while maintaining the ability to build up a plot step by step from multiple data sources.

**Topic:**Data Science, Using R |

**Skill**: Intermediate |

**Credit Options**: CAP, CEU

**Class Start Dates:**Jan 24, 2020, Jul 24, 2020

## Mastery Series

This Mastery Series will give you a deep dive in the Bayesian techniques used to develop statistical software and data analysis.

3-Course Series | Intermediate-Advanced Level

15 CEUs | ACE College Credit Eligible and INFORMS CAP Recognition (select courses)

This mastery series covers the core statistical and analytical models to help you better understand and analyze your business, customer and financial data, and make forecasts and predictions.

3-Course Program | Introductory-Intermediate Level

15 CEUs | ACE College Credit Eligible | INFORMS CAP recognition

This mastery series is a concentrated introduction to the statistical methods used in healthcare.

3-Course Program | Introductory-Intermediate Level

30 CEUs | ACE & CAP College Credit Eligible

This Mastery Series covers topics including forecasting, social network data analysis, and managing the customer lifecycle using data analysis.

3-Course Program | Introductory-Intermediate Level

15 CEUs | ACE College Credit Eligible and INFORMS CAP Recognition

This mastery series covers linear and nonlinear programming, network flow, decision analysis, queuing, and risk simulation.

3-Course Program | Introductory-Intermediate Level

15 CEUs | ACE College Credit Eligible | INFORMS CAP recognition

In this Mastery Series you’ll learn the standard techniques in data mining, the science of learning from data and how to perform predictive modeling using either R, Python, or Excel.

3-Course Program | Introductory-Intermediate Level

15 CEUs | ACE College Credit Eligible | INFORMS CAP Recognition

In this Mastery Series you’ll learn Python programming from the ground up, and you’ll explore foundational concepts in predictive analytics using Python.

3-Course Program | Introductory-Intermediate Level

15 CEUs | ACE College Credit Eligible (select courses) | CAP recognition

This Mastery Series covers how to use R for statistical computing and graphics to read, understand, modify, and create basic and complex functions and translate them into R code.

3-Course Program | Introductory Level

15 CEUs | ACE College Credit Eligible (select courses) | INFORMS CAP recognition

This series will provide you with the skills to design, analyze, and score tests and questionnaires, using similar instruments to measure abilities, attitudes, or other variables.

3-Course Program | Introductory-Advanced Level

15 CEUs

In this Mastery Series provides you will how to use R to map entities using topological, geometric, or geographic properties, and learn how to analyze spatial information.

2-Course Program | Intermediate Level

10 CEUs | ACE College Credit Eligible (select courses) | CAP recognition

This Mastery Series provides a deep dive into how to design, build, and analyze intuitive surveys.

3-Course Program | Introductory-Advanced Level

15 CEUs

This Mastery Series covers the basics of text mining and Natural Language Processing (NLP), and methods of mining and analyzing text data using Python and NLTK – the Natural Language Tool Kit

3-Course Program | Intermediate-Advanced Level

15 CEUs | ACE College Credit Eligible (select courses) | INFORMS CAP Recognition

## Certificates

This certificate program covers everything from forecasting and data visualization to network analysis, risk simulation, and a deep dive in predictive analytics.

8 Required Courses | 2 Electives | 4 Weeks Each

28 Credits | Transferable Via ACE Recomendation Service

This certificate program covers the skills needed to gather, analyze, and assess data for activities like clinical trials, medical research and public health.

7 Required Courses | 3 Electives | 4 Weeks Each

Master’s Degree Equivalent | 28 Credits| Transferable Via ACE

This certificate program will help you master Python and become an expert at building predictive models, machine learning algorithms, and work-based statistical methods.

8 Required Courses | 2 Electives | 4 Weeks Each

Master’s Degree Equivalent | 28 Credits| Transferable Via ACE

This Certificate program will empower you to use Python to build predictive models, develop visualizations, design machine learning algorithms, and integrate statistical methods.

8 Required Courses | 2 Electives | 4 Weeks Each

Master’s Degree Equivalent | 28 Credits| Transferable Via ACE

This certificate program will advance your R programming skills and help you master its use to build predictive models, machine learning algorithms, and unearth customer and predictive analytics, using R.

8 Required Courses | 2 Electives | 4 Weeks Each

Master’s Degree Equivalent | 28 Credits| Transferable Via ACE

This certificate program will empower you to use R to build predictive models, develop visualizations, design machine learning algorithms, and integrate statistical methods in your work or learning practicum.

8 Required Courses | 2 Electives | 4 Weeks Each

Master’s Degree Equivalent | 28 Credits| Transferable Via ACE

This certificate program covers the principal statistical concepts used to design, sample, collect, interpret, and present data as it applies to behaviors of groups of people in their environment and special situations.

7 Required Courses | 3 Electives | 4 Weeks Each

Master’s Degree Equivalent | 28 Credits| Transferable Via ACE

## Degree Programs

General Ed: 60 credits | Area of Study: 34 Credits | Electives: 26 Credits

120 Credits | Bachelor of Science Degree in Data Science and Analytics