İzmir Ekonomi Üniversitesi
  • TÜRKÇE

  • GRADUATE SCHOOL

    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)
    Assistant(s) -
    Course Objectives To introduce important mathematical softwares, to illustrate usage of scientific databases, and to show writing scientific papers.
    Learning Outcomes

    The students who succeeded in this course;

    • will be able to use LaTeX efffectively.
    • will be able to compose scientific papers, tests, CVs effectively.
    • will be able to set up a related software and adapt its usage.
    • will be able to compare and propose different software.
    • 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 Weigthing
    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
    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
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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