Download Data Analytics and Machine Learning for Decision Support

Internship Opportunity
Data Analytics and Machine Learning for Decision
Support Applications
Abstract
Integration Objects is an international company with a strong reputation as a leading systems
integrator and solution provider for data acquisition, process control systems, knowledge
management, decision support systems, diagnosis, expert systems, and industrial networks.
Integration Objects is a leading provider of software products for developing and deploying
intelligent connectivity solutions. Our customers are located in five continents, and include
the largest industrial companies in the world, among the ExxonMobil, Chevron, Total, Saudi
Aramco, and others.
KnowledgeNetTM (KNetTM) is an Integration Objects software application used for data,
information and knowledge sharing, process supervision, plant operation management,
performance management, and more.
Integration Objects is expanding, and we are looking for talented, driven interns to join our
team. In this project, the intern will design and implement an analytic module allowing
application developers to

easily load a huge amount of data,

apply analysis algorithms such as Principle Component Analysis (PCA), Kernel
Principle Component Analysis (KPCA), Partial Least Square (PLS), and Non Linear
Partial Least Square (NLPLS) in order to identify characters dependencies,

apply machine learning algorithms to extract the function that materializes the
behavior of the data,

package the results into a usable function.
The intern will learn how to integrate an analysis and machine learning module into an expert
system using .NET Programming.
Deliverables
At the end of the internship, the intern shall deliver a finalized product with source codes and
documentation:
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

Application source codes (.NET)
Test tools
Documentation: user guide, project report, and test reports
Key words: Analytics, machine learning, PCA, PLS, KPCA, NLPLS
To Apply: please send us your resume, cover letter, marks for previous relevant
courseware, and ranking to: [email protected]