M.SC. in Computer Engineering (Without Thesis)

MATH 600 | Course Introduction and Application Information

Course Name

Mathematics Softwares and Research Methods

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
MATH 600	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Third Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	Lecture / Presentation
National Occupation Classification	-
Course Coordinator	-
Course Lecturer(s)	Doç. Dr. Cemal Murat ÖZKUT
Assistant(s)	-

Course Objectives

To introduce important mathematical softwares, to illustrate usage of scientific databases, and to show writing scientific papers.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	will be able to use LaTeX efffectively.
2	will be able to compose scientific papers, tests, CVs effectively.
3	will be able to set up a related software and adapt its usage.
4	will be able to compare and propose different software.
5	will be able to set up batch programming.

Course Description

The course will focus on the concepts and principles underlying MAGMA computational algebra system and LaTeX, especially the notion of functional programming and pattern matching. This core knowledge will enable attendees to apply researching program system more effectively, and write their papers/course materials with LaTeX. Graduate students will also learn how to use digital databases for research, techniques of mathematical paper writing.

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	An introduction to LaTeX.	George Grätzer, “More Math Into LaTeX”, 5th Edition (Springer, 2016), 3-39.
2	Equations, Picture and table Environments.	George Grätzer, “More Math Into LaTeX”, 5th Edition (Springer, 2016), 43-160, 191-224.
3	Presentations using the beamer package, bibliographic records and citation processing.	George Grätzer, “More Math Into LaTeX”, 5th Edition (Springer, 2016), 234-251, 307-342
4	An introduction to Mathematica	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 1.
5	Basic Consepts, Lists	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 2, chapter 3.
6	Two-Dimensional Graphics, Three-Dimensional Graphics	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 4, chapter 5.
7	Equations	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 6.
8	Midterm
9	Algebra and Trigonometry, Differential Calculus	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 7, chapter 8.
10	Integral Calculus, Multivariate Calculus	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 9, chapter 10.
11	Ordinary Differential Equations, Linear Algebra	Eugene Don, “Schaum's Outline of Mathematica”, 3rd edn (McGraw-Hill, 2018), chapter 11, chapter 12.
12	Simulation Techniques- Monte Carlo Method	Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev, “Handbook of Monte Carlo Methods”, (Wiley, 2011), chapter 1, chapter 2
13	Simulation Techniques- Monte Carlo Method	Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev, “Handbook of Monte Carlo Methods”, (Wiley, 2011), chapter 3, chapter 4
14	Simulation Techniques- Monte Carlo Method	Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev, “Handbook of Monte Carlo Methods”, (Wiley, 2011), chapter 16, chapter 17
15	Semester Review
16	Final Exam

Course Notes/Textbooks

George Grätzer, More Math Into LaTeX, 5th edn (Springer, 2016). ISBN-13: 978-3319237954 Eugene Don, Schaum's Outline of Mathematica, 3rd edn (McGraw-Hill, 2018). ISBN-13: 9781260120738

Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev, “Handbook of Monte Carlo Methods”, (Wiley, 2011). ISBN:9780470177938

Suggested Readings/Materials

T. Oetiker Latex in 157 minutes: The (Not So) Short Introduction to Latex, (Samurai Media Limited, 2015). ISBN-13: 978-9881443625

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4	LO 5
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques	1	20
Portfolio
Homework / Assignments	1	10
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm	1	30
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade	3	60
Weighting of End-of-Semester Activities on the Final Grade	1	40
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	14	3	42
Field Work			0
Quizzes / Studio Critiques	1	24	24
Portfolio			0
Homework / Assignments	2	20	40
Presentation / Jury			0
Project			0
Seminar / Workshop			0
Oral Exam			0
Midterms	1	34	34
Final Exam	1	37	37
		Total	225

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.		-	-	-	X	-
2	Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.		-	-	X	-	-
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.		-	-	-	X	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	-	-	X
5	Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	X
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	-	X	-
7	Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.		-	-	-	X	-
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.		-	-	X	-	-
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	X	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		-	-	X	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		-	-	X	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		-	X	-	-	-