Curricular Proposal

Curricular Structure

In order to obtain a Master’s degree in Computer Science, students must obtain 24 credits in courses, with a minimum of nine credits in courses of the basic group and the remaining can be complementar with courses of the specific group. Students also need to take the course Seminar for Dissertation and Research for Dissertation, both without credit attribution, but compulsory. In the Seminar for Dissertation course, the students present the dissertation proposal, which must be approved by an Examining Board. The students enroll in the Research for Dissertation subject once having their proposal approved, for the elaboration and defense of their dissertation. In the case of scholar students, it is mandatory to comply with the Teaching Internship course. The course is organized on a trimester basis. The above information is contained in the Program standard.

It is worth mentioning the commitment of the PPCIC to train graduates in Computing with skills of data science, in order to extract knowledge from the processing of large data volumes (MDS 2015). In this context, it is a technical-scientific challenge in computing the systematic study for the generalized extraction and in scale of relevant knowledge from an immense mass of data, usually dynamic (Jagadish et al., 2014).

Specifically, we identified two main lines of research whose maturity we believe would lead to the consolidation of the area of Data Science within a horizon of a few years of research and development: (i) Algorithms, Optimization, and Computational Modeling, (ii) Data Management and Applications.

Program Courses

Considering the egress profile of the Program, it aims to train highly qualified human resources and serve as a foundation for its projection in the knowledge society. The PPCIC master’s course offers students a range of computing subjects articulated with the research lines of the Program promoting comprehensive and current training. During the formulation of the PPCIC curricular structure, we compared our proposal to the 23 largest master’s programs in US Data Science (MDS 2015). Furthermore, in the formulation of the courses, we try not to use terms such as BigData and Map-Reduce. We prefer to adopt the corresponding theoretical framework, such as Large Scale Data Management and Parallel and Distributed Computing, respectively.

In the Program’s page, the offered courses are presented, identifying those that are of the basic group and those of the specific group. It should be emphasized that the offer of the courses each trimester is planned and disseminated at the end of the previous year, which allows students to be able to plan how many courses to take.

Innovative Training Experiences

The PPCIC uses educational technologies in the Master’s Program. Their teaching materials are primarily and preferably accessed through the Moodle Platform. Through the platform, students have access to support materials, submit work and interact with each other and teachers. The classrooms were recently equipped with interactive whiteboards with resources for teachers.

Also, there is planning of more significant interaction between undergraduate and postgraduate courses through the undergraduate course called Applied Research Practice. In this course, Master’s students can carry out the Teaching Internship by formulating themes peripheral to their master’s research that are developed by groups of students throughout the class. This theme can also be used as the basis for the conclusion work of the undergraduate course. These initiatives are very positive because they generate a greater synergy between undergraduate and postgraduate, quickly awaken the vocation of collaborative work in Research & Development in masters students and at the same time the interest of undergraduates in improving their training while deciding to take the master’s degree.

Another innovative feature is the Weekly Research Seminar. These seminars aim to stimulate PPCIC students’ ability to organize their research and present their ideas. The seminars take place during each academic term, with the participation of students enrolled in the second trimester of the course onwards. In the seminars, the students present: (i) articles accepted for publication in conferences, for rehearsal purposes; (ii) articles produced in some course in the previous trimester; (iii) an account of the evolution of his research. Through such presentations, students gain feedback on their work and presentations, aiding in their academic development.

The Weekly Research Seminars are integrated into the Scientific Methodology in Computation course. Thus, newcomers have the opportunity to observe in practice the concepts explored in the subject, as well as to know the researches in progress by other students and to allow greater integration between them.

It is also worth mentioning the participation of undergraduate students in the seminars, as an additional activity to their training, through the computation of compulsory hours. Such participation is important, allowing greater integration of these students with the ones from PPCIC. Together with the Applied Research Practice course, the seminars represent yet another stimulus for undergraduates to pursue their masters’ degree.

It is also worth mentioning the interaction with high school students, through the PIBIC-EM Program, effectively seeking the verticalization of education. These students, therefore, have the opportunity to interact with students from other levels of teaching experiencing the practice of research.