Base Knowledge
Not applicable.
Teaching Methodologies
Estão previstas palestras, pelos docentes da unidade curricular ou oradores externos convidados. Está prevista a realização de debates
sobre as temáticas da unidade curricular.
Learning Results
• Understand the concepts of intelligence, intelligent systems and their importance in decision support
• Understand the advantages and technical limitations of new systems and models
• Know knowledge extraction processes, limitations and risks
• Understand the importance, limitations and risks of new digital tools in management and communication
Program
1. Artificial intelligence, knowledge discovery and Decision Support. Cloud, IOT, biometric and non-biometric sensing, Blockchain.
2. Data, models with learning and knowledge.
3. Big Data and Data Mining
4. Social networks. Augmented reality. Digital tools and Human Perception.
5. Classification, detection and prediction models.
Curricular Unit Teachers
Mateus Daniel Almeida MendesGrading Methods
The assessment will be made exclusively on the basis of conducting research work, which must be the subject of mandatory defense.
Internship(s)
NAO
Bibliography
Ryan Light , and James Moody (Eds) (2020), The Oxford Handbook of Social Networks, Oxford University Press
Charles Kadushin (2011), Understanding Social Networks: Theories, Concepts, and Findings, Oxford University Press
Stuart Russell, Peter Norvig (2020) Artificial Intelligence: A Modern Approach (Pearson Series in Artifical Intelligence) 4th Edition, Pearson.
Steven L. Brunton (2019). Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control 1st Edition. Cambridge University Press.
Binto George, Gail Carmichael, Susan Mathai (2021). Artificial Intelligence Simplified: Understanding Basic Concepts Cstrends LLP; 2nd edition.
Alyssa Simpson Rochwerger, Wilson Pang (2021). Real World AI: A Practical Guide for Responsible Machine Learning, Lioncrest Publishing.