Given
Name
Software Development Methodology
When
Fall 2007
Where
ESAF
Duration
16 hours
Name
Software Development Methodology
When
Spring 2007
Where
ESAF
Duration
16 hours
Name
Software Development Methodology
When
Fall 2006
Where
ESAF
Duration
20 hours
Name
Software Development Methodology
When
Spring 2006
Where
ESAF
Duration
20 hours
Name
Design Patterns in Practice
When
Fall 2004
Where
CJR
Duration
10 hours
Name
Design Patterns in Practice
When
Spring 2004
Where
CJR
Duration
10 hours
Name
J2EE
When
Spring 2004
Where
CJR
Duration
10 hours
Name
Java Basic
When
Fall 2003
Where
CJR
Duration
42 hours
Name
Java Basic
When
Spring 2003
Where
FINATEC
Duration
10 hours
Name
Java with Eclipse
When
Spring 2003
Where
FINATEC
Duration
5 hours
Name
Design Patterns
When
Spring 2003
Where
FINATEC
Duration
5 hours
Name
JDBC
When
Spring 2003
Where
FINATEC
Duration
10 hours
Name
RMI
When
Spring 2003
Where
FINATEC
Duration
10 hours
Name
WAS v5 for zOS
When
Spring 2003
Where
FINATEC
Duration
10 hours
Name
Teacher Assistant for Data Structure
When
Spring 2001
Where
UNB
Duration
60 hours
Name
Teacher Assistant for Math
When
Spring 1997
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Grammar
When
Spring 1997
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Physics
When
Spring 1997
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Chemistry
When
Spring 1997
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Math
When
Spring 1996
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Grammar
When
Spring 1996
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Physics
When
Spring 1996
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Name
Teacher Assistant for Chemistry
When
Spring 1996
Where
Marista High School, Brasilia, DF, Brazil
Duration
6 hours
Taken
Name
OR 842 – Models of Probabilistic Reasoning
When
Fall 2009
Where
GMU
Duration
60 hours
Description
Survey of alternative views about how incomplete, inconclusive, and possibly unreliable evidence might be evaluated and combined. Discusses Bayesian, Baconian, Shafer-Dempster, and Fuzzy systems for probabilistic reasoning.
Name
IT 796 – Directed Reading and Research – Semantic Web
When
Fall 2009
Where
GMU
Duration
60 hours
Description
Reading and research on specific topic in information technology under direction of faculty member. This course focused on research in the Semantic Web area.
Name
IT 763 – Research Methods in Systems Engineering and Information Technology
When
Fall 2009
Where
GMU
Duration
60 hours
Description
Examines alternative paradigms of scientific research and their applicability to research in information technology. Topics include fundamental elements of scientific investigation, basic principles of experimental design and statistical induction, philosophy of science and its relation to the information technology sciences, and case studies of information technology research.
Name
OR 750 – Logic Foundation of Knowledge Sharing
When
Summer 2009
Where
GMU
Duration
60 hours
Description
Special topics, applications, or recent developments in operations research. Contents vary and may include topics in optimization, stochastic methods, or decision support that are not covered in the standard OR curriculum. In this course the main topic was Logic.
Name
SYST 664 – Bayesian Inference/Decision Theory
When
Spring 2009
Where
GMU
Duration
60 hours
Description
Introduces decision theory and relationship to Bayesian statistical inference. Teaches commonalities, differences between Bayesian and frequentist approaches to statistical inference, how to approach statistics problem from Bayesian perspective, and how to combine data with informed expert judgment in a sound way to derive useful and policy relevant conclusions. Teaches necessary theory to develop firm understanding of when and how to apply Bayesian and frequentist methods; and practical procedures for inference, hypothesis testing, and developing statistical models for phenomena. Teaches fundamentals of Bayesian theory of inference, including probability as a representation for degrees of belief, likelihood principle, use of Bayes Rule to revise beliefs based on evidence, conjugate prior distributions for common statistical models, and methods for approximating the posterior distribution. Introduces graphical models for constructing complex probability and decision models from modular components.
Name
STAT 554 – Applied Statistics
When
Spring 2009
Where
GMU
Duration
60 hours
Description
Application of basic statistical techniques. Focus is on the problem (data analysis) rather than on the theory. Topics include one and two sample tests and confidence intervals for means and medians, descriptive statistics, goodness-of-fit tests, one- and two-way ANOVA, simultaneous inference, testing variances, regression analysis, and categorical data analysis. Normal theory is introduced first with discussion of what happens when assumptions break down. Alternative robust and nonparametric techniques are presented.
Name
STAT 544 – Applied Probability
When
Fall 2008
Where
GMU
Duration
60 hours
Description
Course in probability with applications in computer science, engineering, operations research, and statistics. Random variables and expectation, multivariate and conditional distributions, conditional expectation, order statistics, transformations, moment generating functions, special distributions, limit theorems.
Name
OR 542 – Stochastic Models
When
Fall 2008
Where
GMU
Duration
60 hours
Description
A survey of probabilistic methods for solving decision problems under uncertainty, probability theory review, reliability, queuing theory, inventory systems, Markov chain models, and simulation. Emphasis on modeling and problem solving.