Title :
A model for advanced in-house industrial training: a case study on intelligent system technology transfer using a project-oriented approach
Author :
Tenorio, Manoel Fernando da Mota ; Maia, Antonio Carlos Pereira ; Grant-Tenorio, Anne Elizabeth
Author_Institution :
Dept. of Electr. & Comput. Eng., New Mexico Univ., Albuquerque, NM, USA
fDate :
5/1/1997 12:00:00 AM
Abstract :
Petroleo Brasileiro SA (PETROBRAS) in conjunction with Synergetics Science and Technology Inc. has developed a comprehensive graduate level educational program in intelligent system design technology. The primary goals of this program are: training professionals to apply artificial intelligence (AI) and neural networks (NN) techniques to managerial and technological problem solving, and to do this in a manner that is both time- and cost-effective. This particular program has been centered around two distinct areas of specialization: symbolic AI and the connectionist approach (NNs). The AI section of the course is titled CAVIAR. The NN section of the course is titled CERN. Short courses and seminars were also part of the program. For this paper, our focus has been to deal with the special needs of graduate-level education in large companies as part of employee professional training. We also explore the nuances of, and the various needs associated with teaching intelligent system design technologies to such a diverse group, as is found in large companies like PETROBRAS. This paper also describes the needs that led to the development of such a broad-based program, the goals and structures of the various courses, the student profiles, educational facilities (libraries and computer laboratories), and the lessons learned. Finally, the conclusion offers recommendations
Keywords :
artificial intelligence; computer science education; educational courses; neural nets; technology transfer; training; CAVIAR; CERN; PETROBRAS; Petroleo Brasileiro SA; Synergetics Science and Technology; artificial intelligence techniques; computer laboratories; connectionist approach; educational facilities; employee professional training; graduate level educational program; in-house industrial training; intelligent system design technology; intelligent system technology transfer; libraries; managerial problem solving; neural networks techniques; project-oriented approach; seminars; short courses; student profiles; technological problem solving; Artificial intelligence; Artificial neural networks; Educational programs; Educational technology; Industrial training; Intelligent systems; Management training; Neural networks; Problem-solving; Technology management;
Journal_Title :
Education, IEEE Transactions on