Artificial Intelligence

5 ECTS / Semester / English

Objectives and competences

Teaching objectives

  1. Promote the use of Artificial Intelligence/pattern recognition tools to solve big data problems in Microbiology;
  2. Increasing the interest in the programming area for the intelligent Microbiological solutions development.

Expected results

The student should be able to:

  1. Know deeply the principles, mechanisms, syntax and semantics of python® programming language;
  2. Recognize the need and the advantages of automatic information processing;
  3. Express themselves correctly in oral and written form about classification and advanced data processing problems, through adequate language and terminology;
  4. Use classification tools for solving data processing problems through the creation of support decision systems.


Teaching Methodologies

Theoretical and practical classes with permanent student involvement.



  1. Python® Programming Language
    - Python® Language Fundamentals
    - Variables, data types and operations
    - Decision and Loop Structures
    - Functions
    - Object oriented Programming
  2. Artificial Intelligence (AI)
    - What is it?
    - The AI main paradigms and challenges
  3. Pattern Recognition Concepts
    - What is machine learning?
    - Learning Problems
    - Overfitting and data store problems
    - Some classic machine learning tools
  4. Supervised Learning
    - Artificial Neural Networks (ANN)
    - Support Vector Machines (SVM)
  5. Unsupervised Learning
    - K-means and Self-organizing maps (SOM)
  6. Theory of Learning and Models/Pattern Selection
    - Cross-validation
    - Genetic Algorithms
    - Pattern sequential selection
    - Statistical Methods
  7. Advanced data analysis and intelligent applications in Microbiology


Assistant Professor
He holds a PhD in Biomedical Engineering from the University of Porto and a MSc and BSc in Biomedical Engineering from the Polytechnic Institute of Bragança. He…