ITEA Professional Development Courses

ITEA Professional Development Courses - ITEA Short Courses, Education, Classes | International Test and Evaluation Association

ITEA provides a variety of professional development formats — including online and face-to-face learning — to help you to maintain, develop or increase your knowledge, problem-solving, technical skills or professional performance standards. These course offerings are also directly mapped to our CTEP certification and the 4 domains that have been identified by our BOE.  Designed to help train new T&E’rs or fill the knowledge gaps for those in need, our courses cover the spectrum.   

ITEA also provides options for bringing live courses, which can be can be tailored to the needs of your organization, to your location which can reduce your training costs up to 50%. For more information on hosting a course on your site, please contact us at  

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Professional Development Short Courses 

The identified course offerings follow and contribute to the knowledge of the 4 subject domains listed below and identified by the Board of Examiners who created the CTEP exam. 

Domain I:  Test and Evaluation Planning

Domain II:  T&E Design

Domain III:  Test and Evaluation Execution

Domain IV:  Test Data Analysis, Evaluation and Reporting


Course Descriptions


Cyber Security and Information Assurance

Domain I,III,IV

This two-day course has been designed for the system engineer, program manager, and IA manager. This course is positioned as a mid-level introduction to cybersecurity and information assurance, and it covers a variety of topics in these areas.  High-risk and labor-intensive processes such as security test & evaluation, and certification and accreditation procedures are covered in detail.  IA risk management is covered across the spectrum of system, C&A, program protection and platform risks, illustrating a useful method of aggregation for comprehensive understanding of IA risk.  The course concludes with a detailed exposition of secure network design and construction principles and techniques that can be applied immediately to existing and new networks and systems. 

The course is fully updated with the latest information on the DoD’s treatment of cybersecurity.  This includes the new implementation of the Risk Management Framework (RMF), the replacement for DIACAP.  The course will cover the new processes, the differences between new and old processes, and methods for accelerating both risk management and risk acceptance.  We will use a detailed example to illustrate how to implement, monitor and test the methods, and we’ll look at risk aggregation as an avenue to understand system of systems risk, collective (control) failure modes, and aggregated system accreditation.

Fundamentals of T&E Processes

Domain I,II

The course will describe the key principles of T&E as a critical part of systems engineering and acquisition.  The current world of T&E has evolved over the last 5 decades from a slogan mantra (“try before buy”) to a set of widely accepted principles and integrated practices.  Industry and government experience has produced processes that enable T&E to be a dependable indicator of progress towards achieving system performance objectives and capabilities during a development program. In the course, you will learn about the key policies and practices that have been adopted, what has triggered them, and what the future holds in this critical arena.  

Operational Design of Experiments (OPDOE) (now additionally offered online!)

Domain I,II

This course will provide the practitioner with the ability to apply the best tools and methods from combinatorial testing and DOE. It will cover the key terminology of DOE and various options to testing, showing why DOE is the most effective and efficient testing approach. This course will cover the activities that must precede a DOE, including the first line of defense against variation and Measurement System Analysis (MSA). Testing strategies, such as screening, modeling, and confirmation, will be discussed along with how they fit into an integrated developmental and operational testing strategy. The 12-step approach to experimental design will be presented to provide a framework for adequately considering all aspects of the test. Basic graphical and statistical analysis of experimental data will be covered. The concept of and need for looking for variance shifting factors will be presented, along with screening designs. Response surface designs such as Box-Behnken and Central Composite Designs will be shown to be more efficient than factorial designs for modeling non-linear responses. Simple Rules of Thumb will be provided for sample size and design selection, along with determining significance and power. Interpreting regression output and the coding of factors and their levels, along with residual analysis, will facilitate the analysis of data not collected under a DOE strategy and provide a means of analyzing data coming from multiple test scenarios. High Throughput Testing (HTT) will provide a combinatorial testing approach that is extremely useful in operational testing when there are many factors, both qualitative and quantitative, each with many levels. Latin Hypercube Sampling and Descriptive Sampling will be shown to be very useful space-filling designs in high dimensions when only a limited number of tests can be conducted. Nearly Orthogonal Latin Hypercube Designs will be discussed and will provide the practitioner with power in screening many variables, such as is the case when dealing with high fidelity simulation models from which low fidelity models can be developed for prediction and risk assessment purposes. This course will cover many examples in the world of test and evaluation and give the student practice at test design and analyzing test results. It will provide the practitioner with the ability and rationale to make good decisions when conducting both developmental and operational tests under a wide variety of circumstances. DOE will be shown to be the science of data collection as it applies to testing and that it must be in the toolkit of every tester.

What T&E’rs Need to Know about Program Management and Systems Engineering and Why

Domain I,II

Test and evaluation have too often and too long been perceived by many practitioners of these disciplines as stand-alone processes. Nothing could be further from the truth, as they are the foundations of developing the knowledge required to conduct effective and efficient program management and systems engineering.  Therefore, testers and evaluators must understand, speak the language of, and properly integrate with the needs and processes of their major customers, the program managers and systems engineers. 

This three-day course presents a basic overview of key program management processes such as leadership, planning, monitoring, control, work breakdown structure, scheduling, budgeting, contracting, and earned value management; and key systems engineering processes such as requirements analysis, functional analysis, partitioning, design, risk management, trade studies, and concurrent and specialty engineering. 

This course also includes discussion of some developing engineering challenge areas such as software engineering and test, human systems engineering, autonomous systems development, and cyber engineering and test. Day 1 discussions cover the basic concepts of program management and systems engineering discussed above. Day 2 is devoted to discussions of the role of test and evaluation in program management and systems engineering, unique aspects of all three disciplines in the Federal Government and DOD, and some case studies of notable DOD acquisition programs. Day 3 discussions examine some interesting and important special topics in DOD acquisition as well as providing a look at the future of DOD acquisition. All of the above subject areas are presented with a perspective that will help ensure that testers and evaluators become better informed and more effective members of any development team.

Probability and Statistics for Reliability/Reliability Growth

Domain I,III,IV

This five-day course covers the concepts and methods to improve a reliability program across the
acquisition life cycle. The focus is on both the proactive approach of designing reliability into the system
up-front, i.e., Design for Reliability (DFR) and monitoring reliability improvements through a reliability
growth process. Students will be able to construct the reliability growth curves now required in Test and
Evaluation Master Plans for major acquisition systems. This course will provide T&E employees with the
basic training needed to understand how reliability methods are implemented in T&E. More specifically,
students will understand the Identify, Design, Optimize, and Validate (IDOV) phases of DFR and will
• Know why reliability is an important metric in today’s business culture
• Know the three basic components of dependability: reliability, availability, maintainability
• Know and be able to describe the major components of the definition of reliability
• Know why testing for failure is the only way to confidently measure and predict product
• Be able to set up, optimize, and interpret the results for reliability
• Understand the three different types of distribution parameters and what they mean
• Know what a probability distribution is and be able to interpret the parameters of selected
probability distributions
• Be able to model failure data using selected probability distributions
• Be able to choose the best distribution for a set of data using curve fitting tools
• Understand the criteria used to evaluate the fit of a distribution

Statistical Methods for Modeling and Simulation Verification and Validation

Domain I,III,IV

This three-day (24 hours) course introduces the students to the statistical tools and methods needed for
the verification and validation of models, including simulation models. Basic statistical concepts will be
introduced and then the course migrates quickly to multivariate analysis, showing how one best builds
statistical models for predicting performance measures based on multiple predictor variables. The
course emphasizes the process for modeling and simulation verification and validation. Exercises and
hands-on activities will demonstrate and reinforce the concepts.