Bachelor Computation and Applied Mathematics

• What will I learn in this course?

  What will I learn in this course?

  1. With the exponential advance in the volume of `big data¿ and its digital transformation over the last decade and a half, we have witnessed and continue to observe a phase of constant reinvention not only of the infrastructures and models of information systems, but also the reinvention of new profiles of professionals in the transformation of data into knowledge. 2. It can be seen that professionals trained in areas related to traditional `Maths¿ have shown a very strong basis for facing this challenge. However, these professionals have made a great effort to adapt to IT infrastructures. 3. The aim is to maintain the analytical thinking of these professionals but also to develop skills in computer engineering.

• Entry requirements and conditions

  Entry requirements and conditions

  Those who apply through the institutional admission process may apply for this study program. See the required exams below.
  
  

  • 16 Matemática
  • and

  or

  • 04 Economia
  • and
  • 16 Matemática
  • and

  or

  • 07 Física e Química
  • and
  • 16 Matemática
  • and

  or

  • 16 Matemática
  • and
  • 18 Português
  • and

  or

  • 02 Biologia e Geologia
  • and
  • 16 Matemática
  • and

  or

  • 09 Geografia
  • and
  • 16 Matemática
  • and

  or

  • 13 Inglês
  • and
  • 16 Matemática
  • and

  
  Pass in one of the following sets of entrance exams: Maths (16) or Maths (16) and Economics (04) or Maths (16) and Physics and Chemistry (07) Candidates can also enter through the change of institution/course pair system, or through a Special Competition, in accordance with the legal rules in force. according to the legal rules in force (holders of higher education courses, holders of CETs, holders of CTSPs, over 23s, holders of dual certification courses). courses). Candidates who fulfil the conditions laid down in the International Student Statute may also enter.

• Technical and professional skills that I will acquire

  Technical and professional skills that I will acquire

  1. Theoretical, methodological and practical foundations in the areas of computer science, applied mathematics and computer engineering. In particular: Maths, Statistics, Machine Learning, Artificial Intelligence and Computer Engineering. 2. Know how to handle large volumes of data within data protection laws, create and implement new and current algorithms and mathematical models in A.I. 3. Obtain scientific quality results with fluidity; know how to integrate and work in multidisciplinary teams; good synthesis skills.

• Study plan and curriculum structure

  Study plan and curriculum structure

  • 1º Ano / Common Core
    • [1º Semestre]
    • Data Science Foundations 6 ects
    • Discrete Mathematics 6 ects
    • Introduction to Mathematical Probability 6 ects
    • Mathematics I 6 ects
    • Programming Fundamentals 6 ects

    • [2º Semestre]
    • Exploratory Data Analysis 6 ects
    • Linear Algebra 6 ects
    • Mathematics II 6 ects
    • Numerical Analysis 6 ects
    • Programming Languages 6 ects
  • 2º Ano / Common Core
    • [1º Semestre]
    • Algorithms and Data Structures 6 ects
    • Databases 6 ects
    • Introduction to Computer Science 6 ects
    • Introduction to Ordinary Differencial Equations 6 ects
    • Introduction to the Theory of Graphs and Networks 6 ects

    • [2º Semestre]
    • Fundaments of Data Engineering for Data Science 6 ects
    • Introduction to Stochastic Processes 6 ects
    • Machine Learning I 6 ects
    • Statistical Methods 6 ects
    • Visualization for Data Science 6 ects
  • 3º Ano / Common Core
    • [Anual]
    • Final Course Work 20 ects

    • [1º Semestre]
    • Machine Learning II 5 ects
    • Option I
    • Option II
    • Option III

    • [2º Semestre]
    • Cloud Information Systems 5 ects
    • Computer Networks 5 ects
    • Operational Research 5 ects
    • Option IV

• Options

  Options

  • Option I
    • Abstract Algebra (Option I) 5 ects
  • Option II
    • Introduction to Privacy, Security and Ethics (Option II) 5 ects
    • Scientific Research Methodologies (Option II) 5 ects
  • Option III
    • Artificial Intelligence (Option III) 5 ects
  • Option IV
    • Introduction to Fuzzy Logic (Option IV) 5 ects

• Course Team

  Course Team

  Aleksandar Mikovic

  Ana Cruz

  Andre Fonseca

  Bruno Saraiva

  Carlos Iglésias

  Carlos Fernandes

  Giosuè Muratore

  Henrique Navas

  Iolanda Velho

  José Paredes

  João Caldeira

  João Craveiro

  João Moreira

  Luis Gomes

  Luís Campos

  Marcelo Domingues

  Maria Silva

  Marina Martins

  Rui Ribeiro

  Sofia Naique

  Thiago Paiva

  Zuil Filho

  See all teachers

• Career opportunities and career prospects

  Career opportunities and career prospects

  Data Scientist Computer Scientist Business Intelligence Analyst Machine Learning & A.I. Scientist Solid background to pursue a Ph.D programme.

• Scientific areas of the course

  Scientific areas of the course

  Ciências informáticas

• Observations

  Observations

  Assessment methodology The programme offers a strong technical introduction to the student in the areas mentioned, through methodologies: (1) Expository, (2) Experimental, (3) Active, promoting teamwork and (4) Self-Study. Teaching Model B-learning (Mixed)

Department of Computer Engineering and Information Systems

• DEISI Website