COURSE INFORMATION Course Title: ADVANCED TOPICS IN COMPUTER ENGINEERING

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
CEN 804	C	99	3	2	0	4	7.5

Language:	English
Compulsory/Elective:	Elective
Classroom and Meeting Time:	Thu 10:00-12:00
Course Description:	-
Course Objectives:	The objective of this course is to enable the students to conduct research of their interest under the supervision of their advisor.

COURSE OUTLINE

Week	Topics
1	Methods of Linear Algebra
2	Statistical Learning Theory
3	Unsupervised Learning Models
4	Unsupervised Learning Models
5	Supervised Learning Models
6	Supervised Learning Models
7	Paper Review
8	Paper Review
9	Presentations
10	Presentations
11	Presentations
12	Presentations
13	Presentations
14	Presentations

Prerequisite(s):
Textbook:
Other References:
Laboratory Work:
Computer Usage:
Others:	No

COURSE LEARNING OUTCOMES

1	Learn how to use Advanced Linear Algebra techniques in Data Analysis
2	Learn how to analyse using Statistical Learning Theory
3	Solving problems using unsupervised and supervised learning models

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Doctorate (PhD) in Computer Engineering Program
1	Engineering graduates with sufficient theoretical and practical background for a successful profession and with application skills of fundamental scientific knowledge in the engineering practice.	5
2	Engineering graduates with skills and professional background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations	5
3	Engineering graduates with the necessary technical, academic and practical knowledge and application confidence in the design and assessment of machines or mechanical systems or industrial processes with considerations of productivity, feasibility and environmental and social aspects.	4
4	Engineering graduates with the practice of selecting and using appropriate technical and engineering tools in engineering problems, and ability of effective usage of information science technologies.	4
5	Ability of designing and conducting experiments, conduction data acquisition and analysis and making conclusions.	5
6	Ability of identifying the potential resources for information or knowledge regarding a given engineering issue.	3
7	The abilities and performance to participate multi-disciplinary groups together with the effective oral and official communication skills and personal confidence.	4
8	Ability for effective oral and official communication skills in foreign language.	4
9	Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology.	4
10	Engineering graduates with well-structured responsibilities in profession and ethics.	4
11	Engineering graduates who are aware of the importance of safety and healthiness in the project management, workshop environment as well as related legal issues.	3
12	Consciousness for the results and effects of engineering solutions on the society and universe, awareness for the developmental considerations with contemporary problems of humanity.	4

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Homework	3	5
Presentation	3	10
Project	1	40
Case Study	1	5
Term Paper	1	10
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	5	80
Hours for off-the-classroom study (Pre-study, practice)	16	2	32
Mid-terms	1	15	15
Assignments	3	12	36
Final examination	1	24.5	24.5
Other			0
Total Work Load:			187.5
Total Work Load/25(h):			7.5
ECTS Credit of the Course:			7.5