UNIVERSIDADE FEDERAL DE CAMPINA GRANDE | 2020-2021
The main goal of my M.Sc. was to develop a new Pattern recognition system to detect and predicts the urban growth. Thus, an anomaly detection system was proposed, through satellite images besides Computer Vision and Machine Learning techniques. The final results confirmed that we were able to track identifiers of changes in the earth’s surface temporally with satisfactory results.
INSTITUTO FEDERAL DE EDUCAÇÃO, CIENCIA E TECNOLOGIA DE ALAGOAS | 2018-2019
- Activities: Evaluation of Predictive Regression Models to Estimate Software Effort
- GPA: 87.83 (in a 1-100 scale, not graded on a curve)
Professionals are able to handle scope changes in the construction cycle applying dynamic and innovative methods and techniques in the development and management in the context of agile teams, as an alternative to the traditional Software Engineering.
UNIVERSIDADE ESTÁCIO DE SÁ | 2015-2017
- Activities: Pillars of Data Analytics and their application in companies (Em Português)
- GPA: 87.50 (in a 1-100 scale, not graded on a curve)
To specialize and to qualify professionals of Computer science in Administration of Database, giving to the students the integration of theoretical and practical knowledge with emphasis in architecture of DBMS. To prepare the student, through studies and practices on specific knowledge of a commercial DBMS, for certification tests.
INSTITUTO FEDERAL DE EDUCAÇÃO, CIENTCIA E TECNOLOGIA DE ALAGOAS | 2010-2015
- Activities: Build a web system based on Domain Driven Desing
- GPA: 72.90 (in a 1-100 scale, not graded on a curve)
Professionals are able to handle scope changes in the construction cycle applying dynamic and innovative methods and techniques in the development and management in the context of agile teams, as an alternative to the traditional Software Engineering.
CERTIFICATIONS
ENGLISH LANGUAGE AND LITERATURE PROFICIENCY (2011-2016)
Proficiency in reading, grammar, writing and speaking.
HONOR & AWARD
NATIONAL
2nd place - Runner-up, WPOS-CSBC Workshop - 2017
A Predictive Analysis Approach Using Linear Regression To Estimate Software Effort - Making decisions with a highly uncertain level is a critical problem in the area of software engineering. Predicting software quality requires high accurate tools and high-level experience. AI-based predictive models, on the other hand, are useful tools with an accurate degree that help to make decisions learning from past data. In this study, we build a software effort estimation model to predict the effort before the project development lifecycle, using a linear regression model and also using non-parametric validation model through a Knn regression algorithm.