SLO | EN

Objectives and competences

The student will learn methods of intelligent system design, implementation and use focused on modern machine learning techniques.

Content (Syllabus outline)

• Concepts of intelligent system design. • Applications of IS • Implementation of IS components in modern tools (e.g. ‘R’) • Data acquisition for IS • Advanced knowledge representations and machine learning techniques: o Symbol-based methods, o Connectivist methods, o Association rules, o Bayes classifiers, o Hybrid methods, • Transition from classic connectivist methods to deep learning • Upgrading knowledge models • Prediction in dynamic systems and chaos theory. • Cellular automata. • Nature-based intelligent systems. • Evaluation, ethical questions and challenges. • Functional safety for IS

Learning and teaching methods

• lectures, • lab work.

Intended learning outcomes - knowledge and understanding

• Present the knowledge of advanced techniques of intelligent system design, implementation and evaluation, • Understane the safety concept in intelligent systems, • Use computer tools for data preparation, • Analyse the results of use of intelligent systems, • Use the knowledge of intelligent systems for more efficient problem solving

Intended learning outcomes - transferable/key skills and other attributes

Use of information technology: implementation of intelligent systems. Problem solving: the design and implementation of research studies.

Readings

• I. H. Witten, E. Frank, M.A. Hall: Data Mining, Practical Machine Learning Tools and Techniques, Morgan Kaufmann, Burlington, 2011. • M. Zorman, et al: Inteligentni sistemi in profesionalni vsakdan, Univerza v Mariboru, Center za interdisciplinarne in multidisciplinarne raziskave in študije, Maribor, 2003. • J. Han, M. Kamber, J. Pei: Data Mining: Concepts and Techniques, Morgan Kaufmann, San Francisco, 2012.

Prerequisits

Recommended are Basic skills in machine learning and artificial intelligence.

  • red. prof. dr. MILAN ZORMAN, univ. dipl. inž. rač. in inf.

  • Written examination: 50
  • Laboratory work: 50

  • : 30
  • : 30
  • : 120

  • Slovenian
  • Slovenian

  • COMPUTER SCIENCE AND INFORMATION TECHNOLOGIES - 1st
  • INFORMATICS AND DATA TECHNOLOGIES - 1st