Click to Print This Page
Code MATH 204
Term 201602
Title Discrete Mathematics
Faculty Faculty of Engineering and Natural Sciences
Subject Mathematics(MATH)
SU Credit 3
ECTS Credit 6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Michel Lavrauw,
Detailed Syllabus
Language of Instruction English
Level of Course Undergraduate
Type of Course Click here to view.
(only for SU students)
Mode of Delivery Formal lecture,Recitation
Planned Learning Activities Interactive,Communicative

Introduction to combinatorial problems and techniques. Sets, relations and functions. Graphs, trees, matching, network flows. Counting techniques. Recurrence relations and generating functions. Combinatorial circuits and finite state machines. Also part of the "core course" pools for the CS, MS,TE degree programs.


This course aims to introduce basic ideas of discrete mathematics such as formal mathematical reasoning techniques, basic counting techniques, relations, graphs and trees. The course gives students training to develop their mathematical skills, analytical and critical thinking abilities, their ability to apply these capabilities to practical problems, and to communicate their knowledge of these areas.

Learning Outcome

On completion of this course the student should be able to:
Understand the notion of mathematical thinking, mathematical proofs, algorithmic thinking, and able to apply them in problem solving.

Present simple proofs in a precise and formally correct way
Apply various methods of prof like mathematical induction, direct, indirect proofs.
Understand the basic concept of an algorithm and apply appropriate algorithms to solve problems in combinatorial mathematics.
Understand asymptotic notation, its significance, and be able to use it to analyse asymptotic performance for some basic algorithmic examples.
Use definitions to solve problems and prove statements in elementary number theory.
Understand the principle of recursion and apply it to the study of sequences and sets.
Understand the basic properties of graphs and trees and use these concepts to model simple applications.
Understand the principles of counting.

Programme Outcomes
Common Outcomes For All Programs
1 Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 1
2 Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4
3 Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 2
4 Communicate effectively in Turkish and English by oral, written, graphical and technological means. 3
5 Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 2
Common Outcomes ForFaculty of Eng. & Natural Sci.
1 Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 4
2 Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 3
3 Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 2
4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 1
5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 1
6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 1
7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 1
Computer Science and Engineering Program Outcomes Required Courses
1 Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 1
2 Demonstrate knowledge of discrete mathematics and data structures. 5
3 Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 1
Molecular Biology, Genetics and Bioengineering Program Outcomes Core Electives
1 Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1
2 Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1
Electronics Engineering Program Outcomes Core Electives
1 Use mathematics (including derivative and integral calculations, probability and statistics), basic sciences, computer and programming, and electronics engineering knowledge to design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software. 1
2 Analyze and design communication networks and systems, signal processing algorithms or software using advanced knowledge on differential equations, linear algebra, complex variables and discrete mathematics. 1
Industrial Engineering Program Outcomes Core Electives
1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 1
2 Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 1
3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 1
Materials Science and Nano Engineering Program Outcomes Area Electives
1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1
2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1
3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1
Mechatronics Engineering Program Outcomes Area Electives
1 Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 1
2 Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 1
Assessment Methods and Criteria
  Percentage (%)
Final 35
Midterm 45
Exam 15
Participation 5
Recommended or Required Reading

Kenneth H. Rosen, Discrete Mathematics and Its Applications, McGraw-Hill


1. Ronald L. Graham, Donald E. Knuth, Oren Patashnik,
Concrete Mathematics, Addison-Wesley

2. Alan Tucker, Applied Combinatorics, John Wiley Sons