MATH209 Discrete Mathematics II

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Course Code Course Title Weekly Hours* ECTS Weekly Class Schedule
Prerequisite None It is a prerequisite to


Lecturer Emin Tahirović Office Hours / Room / Phone

Currently not available

Assistant Assistant E-mail
Course Objectives The objective of this course is to train students discrete mathematics techniques and problem-solving skills necessary for further training in computer science and software engineering careers. The course is a blend of mathematics and problem-solving, focusing on graph theory and combinatorics.
Textbook Applied Combinatorics by Alan Tucker, 6th Edition.
Additional Literature
Learning Outcomes After successful  completion of the course, the student will be able to:
  1. Define and understand basics of graph theory.
  2. Understand combinatorial structures and games with graphs.
  3. Analyze and understand the connection between induction and recursive algorithms.
  4. Analyze complexity of recursive algorithms
  5. Be able to recognize a problem as a graph or a combinatorial type problem
Teaching Methods Class discussions with examples. Active tutorial sessions for engaged learning and continuous feedback on progress. Active lab involve real algorithms, analysis, interpretation.
Teaching Method Delivery Teaching Method Delivery Notes
Week 1 Course introduction
Week 2 Elements of graph theory Chapter 1
Week 3 Covering circuits and graph coloring Chapter 2
Week 4 Trees and Searching Chapter 3
Week 5 Network algorithms/Max-Flow Min-Cut Chapter 4
Week 6 General Counting Methods for arrangements and selections Chapter 5
Week 7 Mid-term
Week 8 Recurrence relations Chapter 7
Week 9 Master method Notes
Week 10 Polya's Enumeration Formula Chapter 9
Week 11 Games with graphs Chapter 10
Week 12 Probability Notes
Week 13 Probability and data structures & algorithms Notes
Week 14 Mini project presentations Notes
Week 15 Review Notes
Assessment Methods and Criteria Evaluation Tool Quantity Weight Alignment with LOs
Final Exam 1 40 1,2,3,4,5
Semester Evaluation Compenents
Mid-term 1 35 1,2,3,4,5
Mini project 1 15 1,2,3,4,5
HW 10 10 1,2,3,4,5
***     ECTS Credit Calculation     ***
 Activity Hours Weeks Student Workload Hours Activity Hours Weeks Student Workload Hours
Lecture Hours 3 15 45 Labs 2 15 30
Mini project 20 1 20 HW 1 10 10
Tests study 3 15 45
        Total Workload Hours =
*T= Teaching, P= Practice ECTS Credit =
Course Academic Quality Assurance: Semester Student Survey Last Update Date: 16/04/2021
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