Systems of linear equations; Gaussian elimination. Vector spaces, subspaces, linear, independence, dimension, change of basic. Linear transformations. Inner product, orthogonality. Eigenvalues. Diagonalization and canonical forms. Cayley-Hamilton theorem.

### Linear Algebra (MATH 201)

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Programs\Type | Required | Core Elective | Area Elective |

BA- Political Science | |||

BA-Cultural Studies | |||

BA-Cultural Studies | |||

BA-Economics | |||

BA-Economics | |||

BA-International Studies | |||

BA-International Studies | |||

BA-Management | |||

BA-Management | |||

BA-Social & Political Sciences | |||

BA-Visual Arts&Visual Com.Des. | |||

BA-Visual Arts&Visual Com.Des. | |||

BS-Biological Sci.&Bioeng. | * | ||

BS-Computer Science & Eng. | * | ||

BS-Computer Science & Eng. | * | ||

BS-Electronics Engineering | * | ||

BS-Electronics Engineering | * | ||

BS-Industrial Engineering | * | ||

BS-Manufacturing Systems Eng. | * | ||

BS-Materials Sci. & Nano Eng. | * | ||

BS-Materials Science & Eng. | * | ||

BS-Mechatronics | * | ||

BS-Mechatronics | * | ||

BS-Microelectronics | * | ||

BS-Molecular Bio.Gen.&Bioeng | * | ||

BS-Telecommunications | * | ||

Mathematics | * |

### CONTENT

### OBJECTIVE

This course aims to introduce basic concepts of linear algebra such as vector spaces, bases, linear transformations, eigenvalues and eigenspaces. 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

Understand the notion of mathematical thinking, mathematical proofs, and able to apply them in problem solving.

Present simple proofs in a precise and formally correct way.

Solve a system of linear equations using matrix reduction

Do basic arithmetical operations with matrices.

Understand the notions of linear independence, basis and dimension of a vector space.

Find a basis and dimension of Euclidean or abstract vector spaces.

Geometrically interpret the above concepts.

Represent linear transformations as matrices and, conversely, interpret matrices as linear maps.

Compute determinant of square matrices and understand the properties of determinant.

Compute eigenvalues and eigenspaces of matrices.

Identify whether a matrix is diagonalizable or not.

### PROGRAMME OUTCOMES

**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. 2

**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. 1

**4.** Communicate effectively in Turkish and English by oral, written, graphical and technological means. 1

**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. 1

**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. 1

**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

**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

**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. 4

**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

**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. 3

**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. 1

**3.** Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 1

**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

**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

### Update Date:

### ASSESSMENT METHODS and CRITERIA

Percentage (%) | |

Final | 30 |

Midterm | 50 |

Exam | 20 |

### RECOMENDED or REQUIRED READINGS

Textbook |
G. Strang, Introduction to Linear Algebra. Fifth edition (2016) Wellesley-Cambridge Press and SIAM |

Readings |
Anton H., Rorres C., ?Elementary Linear Algebra with supplemental applications?, Wiley International Student Version, 11th edition, 2015. Bretscher O., ?Linear Algebra with Applications?, 2nd Edition, Prentice-Hall, 2001. Poole D., ?Linear Algebra: A Modern Introduction? 3rd Edition, Brooks Cole, 2011. Leon, S. J., Linear Algebra with Applications, 9th Edition, Prentice Hall, 2014. Kolman B., Hill D., ?Elementary Linear Algebra witg Applications?, 9th edition, Prentice-Hall, 2008. Takahashi S, Inoue I, ?The Manga Guide to Linear Algebra?, 2012. Gilbert Strang lectures on linear algebra, Lectures 1-34, Spring 2005, |