Brazil currently occupies the sixth largest world market for information and communication technology (ICT) (ABES 2016). It is estimated that the ICT sector has grown by US $ 152 billion in 2015. This positive scenario generates demand for the formation of qualified human resources, requiring planning and greater investments. In addition, a high degree of innovation and research is needed if the country is to reach increasingly prominent international positions. In this sense, it is of national interest to intensify postgraduate programs aimed at training masters and doctors with a higher degree of specialization in strategic sectors of Computing.
It is also observed that there is a demand by computer professionals increasingly able to extract knowledge from large volumes of data, so-called data scientists (Davenport and Patil 2012; DSC 2015). It can be said that several companies are urging the hiring of data scientists. They are immersed in the deluge of data (from English, Data Deluge) (Berman 2008), where there is a great deal of data, with different types of information on an unprecedented scale. This demand for these Computer Science experts is well ahead of the supply capacity. The treatment of the data deluge being produced by the sciences and billions of users of global Internet services presents itself as one of the great challenges for the current knowledge society. In the business world, data scientists are key players in the Big Data scenario (Jagadish et al., 2014). They are able to structure this data and find patterns to advise executives on the implications for products, processes, and decisions (Dhar 2013).
In fact, the demand for data scientists is much broader. The deluge of data is generally manifold in multiple facets, a fact that has been driving initiatives in several areas, in addition to the business world, in order to better understand it. In the sciences, the data deluge appeared as the expression of a new way of research (Wright 2014), encouraging biologists, astronomers, physicists, and other researchers from different scientific areas to face computational problems in the so-called e-science, which become Barriers to their findings. In the government sector, there are opportunities to look at huge public sector databases to generate more efficient planning as well as new services that can improve citizen service. The data scientist is, therefore, a professional trained mainly in the analysis, interpretation and manipulation of large volumes of data (MDS 2015), in order to bring the scientific method to the most different sectors aiming the generalized extraction of relevant knowledge to From these data (Jacobs 2009; Lazer et al., 2014).
In order to meet this demand and, at the same time, considering the skills and competences of its faculty, it is the beginning of the Graduate Program in Computer Science (PPCIC) in June 2016. The PPCIC begins with a Master’s degree stricto sensu (academic master’s degree), being organized on a quarterly basis. To obtain a Master’s degree in Computer Science, students of the Program must obtain 24 credits in disciplines, develop a qualified scientific production and defend both a qualification examination and the master’s dissertation itself.
Given this contextualization focused on the challenges of Data Science, the program combines basic and applied research. This is a characteristic designed both for the profile of the egress and also present in the profile of the researchers of the current faculty and expected for the future teachers to be incorporated into the program. This combination establishes a promising strategy, since at the same time as theoretical results are established that subsidize the construction of new applications to solve practical questions, practical problems often lead to the development of new theoretical frameworks. This approach adopted by our group is adherent to the multidisciplinary process of Computing.
The program is part of the Computer Science knowledge area and is organized in the lines of Algorithms, Optimization, and Computational Modeling and Data Management and Applications.
The Line of Data-Based Methods comprises all individual steps from data selection to knowledge extraction. The Data and Applications Management line comprises the entire framework that establishes the in-silico experiment from a datacentric perspective.
While the Algorithms, Optimization, and Computational Modeling line is agnostic to the problem domain, the Data Management and Applications line is dependent on the problem addressed and strongly multidisciplinary. Thus, Data-Based Methods have a broad aspect of serving as basic research. Already, the line of data and application management has a broader bias of applied research impacting different areas of knowledge and in sectors of action along the science-industry-government axis.
CEFET/RJ – Celso Suckow da Fonseca Federal Center of Technological Education – is a Federal Institution of Higher Education (HEI). Currently, the Institution has eight Post-Graduation Programs stricto sensu with the offer of six academic Masters courses, four PhD courses and one Professional Master’s degree; Six postgraduate courses lato sensu; 11 Undergraduate courses in Computing, Engineering and Administration; Two courses of Licentiate in Physics and 31 courses of technical education, distributed in the Headquarters Unit (Maracanã) and in seven Decentralized Teaching Units (Nova Iguaçu, Maria da Graça, Petrópolis, Nova Friburgo, Valença, Angra dos Reis and Itaguaí) . CEFET/RJ also operates in the distance education modality, with participation in the Open University of Brazil (UAB), offering a specialization course in Technological Education aimed at the training of teachers who work in basic education, and the CEDERJ Consortium Superior to Distance from Rio de Janeiro), which brings together federal and state public universities in the State of Rio de Janeiro.
At that moment, when the Federal Network of Professional, Scientific and Technological Education was consolidated, CEFET/RJ made the option of not transforming into a Federal University of Education, Science and Technology (FI) , Which has the formal support of ANDIFES and the Forum of Pro-Rectors of Research and Post-Graduation (FOPROP). In line with the goal of becoming a Technological University, CEFET/RJ’s General Directorate has been investing heavily in research and in graduate studies, being aware of the strategic role of such activities in a university model. This support can be seen through a significant increase in own resources for the needs of research groups and postgraduate programs. This commitment to the consolidation of research and graduate studies in the Institution is formalized in its Institutional Development Plan (IDP).
The strong growth of research and graduate activities in CEFET/RJ observed in recent years can be translated by the significant increase in qualified scientific production, the number of research groups, the number of postgraduate programs, the number of fellows Productivity of CNPq, the number of scientific and master’s degree fellowships, and the expansion of its research infrastructure with the creation of new laboratories and the modernization of existing ones. The renewal of the teaching staff in recent years was an essential factor in promoting the increase of faculty in the institution, especially those with a doctorate degree. This scenario directly influences the prospects for the evolution and consolidation of PPCIC.