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13M111TA - Theory of Algorithms

Course specification
Course title Theory of Algorithms
Acronym 13M111TA
Study programme Electrical Engineering and Computing
Module Applied Mathematics, Audio and Video Technologies, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics and Digital Systems, Energy Efficiency, Information and Communication Technologies, Microwave Engineering, Nanoelectronics and Photonics, Power Systems - Networks and Systems, Power Systems - Renewable Energy Sources, Power Systems - Substations and Power Equipment, Signals and Systems, Software Engineering
Type of study master academic studies
Lecturer (for classes)
  • professor PhD Milo Tomašević
Lecturer/Associate (for practice)
  • professor PhD Milo Tomašević
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition Algorithms and Data structures 1 and 2
    The goal Intoducing the students to the advanced concepts of algorithm theory, the analysis and implementation of algorithms from specific classes.
    The outcome Deep knowledge and understanding of algorithms from several relevant classes, ability of analysis and an efficient implementation.
    Contents
    Contents of lectures About algorithms and data structures. Paradigms, design, and analysis of algorithms. Advanced data structures. Manipulation with strings and sets. Advanced graph algorithms. Geometrical algorithms. Parallel algorithms. Compression. Approximation algorithms. Randomization algorithms. Genetic algorithms. Dynamic and linear programming.
    Contents of exercises Demonstration of algorithm functioning in visual simulators. Solving practical problems. Implementation of algorithms and their performance evaluation.
    Literature
    1. Cormen, Leiserson, Rivest, Intoduction to Algorithms, 3rd edition, MIT Press, 2009.
    2. Sedgewick, Algorithms, 4th edition. Addison Wesley, 2011.
    3. Kleinberg, Tardos, Algorithm Design, Pearson, 2006. (Original title)
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    2 2
    Methods of teaching auditory class lessons and exercises with presentations, lab exercises, homeworks
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 0 Test paper 60
    Practical lessons 40 Oral examination 0
    Projects
    Colloquia
    Seminars 0