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Course Description Course Name : Advanced Computing Theory Course Code : CENG-532 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Prof.Dr. MEHMET TÜMAY Learning Outcomes of the Course : Understands the advanced computer architecture. Understands algorithim design Familiarizes with knowledge representation and reasoning. Learns mobile device programming. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : Knowledge and skills acquisition about software development, project estimation, implementation and management. Course Contents : Advanced computer architecture, algorithim design, computer graphics, knowledge representation and reasoning, foundations of programming mini-project, methods for understanding users in computer science, simulation for computer scientists, software project management Language of Instruction : English Work Place : Computer Engineering Department, First Floor   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Advanced computer architecture Lecture notes and resources Classical lecture and presentation 2 Algorithim design Lecture notes and resources Classical lecture and presentation 3 Computer Graphics Lecture notes and resources Classical lecture and presentation 4 Mixed, virtual and augmented reality Lecture notes and resources Classical lecture and presentation 5 Introduction to human computer interaction Lecture notes and resources Classical lecture and presentation 6 Knowledge representation and reasoning Lecture notes and resources Classical lecture and presentation 7 Operations research and modelling Lecture notes and resources Classical lecture and presentation 8 Midterm examination Preparation for midterm examination Written examination 9 Advanced computer communications Lecture notes and resources Classical lecture and presentation 10 Automated scheduling Lecture notes and resources Classical lecture and presentation 11 Data mining techniques and applications Lecture notes and resources Classical lecture and presentation 12 Designing intelligent agents Lecture notes and resources Classical lecture and presentation 13 Foundations of programming mini-project Lecture notes and resources Classical lecture and presentation 14 Fuzzy sets and fuzzy logic systems Lecture notes and resources Classical lecture and presentation 15 Methods for understanding users in computer science Lecture notes and resources Classical lecture and presentation 16/17 Final Examination Preparation for final examination Written examination   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Advanced Computing, N. Meghanathan, B. K. Kaushik, D. Nagamalai, Conference Book, 2011 Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 90     Homeworks/Projects/Others 5 10 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Reaches wide and deep knowledge through scientific research in the field of computer engineering, evaluates, implements, and comments. 4 2 Describes and uses information hidden in limited or missing data in the field of computer engineering by using scientific methods and integrates it with information from various disciplines. 3 3 Follows new and emerging applications of computer engineering profession, if necessary, examines and learns them 3 4 Develops methods and applies innovative approaches in order to formulate and solve problems in computer engineering. 3 5 Proposes new and/or original ideas and methods in the field of computer engineering in developing innovative solutions for designing systems, components or processes. 4 6 Designs and implements analytical modeling and experimental research and solves the complex situations encountered in this process in the field of Computer Engineering 4 7 works in multi disciplinary teams and takes a leading role and responsibility. 4 8 Learns at least one foreign language at the European Language Portfolio B2 level to communicate orally and written 3 9 Presents his/her research findings systematically and clearly in oral and written forms in national and international meetings. 3 10 Describes social and environmental implications of engineering practice. 2 11 Considers social, scientific and ethical values in collection, interpretation and announcement of data. 3 12 Acquires a comprehensive knowledge about methods and tools of computer engineering and their limitations. 4 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 5 70 Assesment Related Works     Homeworks, Projects, Others 5 6 30     Mid-term Exams (Written, Oral, etc.) 1 3 3     Final Exam 1 3 3 Total Workload: 148 Total Workload / 25 (h): 5.92 ECTS Credit: 6