TEXTILE AND FASHION DESIGN
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
CMP4501 Introduction to Artificial Intelligence and Expert Systems Spring 3 0 3 6
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Assist. Prof. BARIŞ ÖZCAN
Recommended Optional Program Components: None
Course Objectives: The course introduces basics of artificial intelligence. Basic search techniques used for problem solving, fundamentals of knowledge representation and logical formalisms, basic learning algorithms, and fundamentals of expert systems will be introduced.

Learning Outcomes

The students who have succeeded in this course;
I. Be able to formulate a state space description of a problem
II. Be able to select and implement brute-force or heuristic algorithm for a problem.
III. Be able to implement minimax search with alpha-beta pruning.
IV. Be able to compare and evaluate the most common models for knowledge representation.
V. Be able to explain the operation of the resolution technique for theorem proving.
VI.Be able to explain the differences among supervised and unsupervised learning.
VII. Be able to explain the concepts of overfitting, underfitting, bias, and variance.
VIII. Be able to implement some of the basic algorithms for supervised learning and unsupervised learning.
IX. Be able to describe fundamentals of expert systems and evaluate them.

Course Content

Introduction to AI, state spaces and searching, heuristic functions and search, alpha-beta pruning, propositional and first-order predicate logic, propositional and first order inference, unification and resolution, linear regression, logistic regression, neural networks and backpropagation algorithm, Bayes’ rule and naive Bayes algorithm, clustering and k-means algorithm, fundementals of expert systems, software for expert systems.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction to AI
2) State spaces and searching.
3) Constraint Satisfaction Problems
4) Searching with other agents.
5) Markov decision processes I
6) Markov decision processes II
7) Midterm
8) Reinforcement Learning
9) Probability, Bayes' Rule and Bayes Nets
11) Bayes’s rule and naive Bayes algorithm.
12) Neural networks and backpropagation algorithm I
13) Neural Networks and backpropagation algorithm II
14) Large Language Models I
15) Large Language Models II

Sources

Course Notes / Textbooks: Russell, S., Norvig, P., Artificial Intelligence: A Modern Approach, (3rd edition), 2009.

Giarratano, J.C., Riley, G.D., Expert Systems: Principles and Programming, (4th edition), 2004.
References: Yok - None

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Quizzes 5 % 20
Project 1 % 25
Midterms 1 % 20
Final 1 % 35
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Project 7 35
Homework Assignments 10 20
Quizzes 6 16
Midterms 5 15
Final 5 20
Total Workload 148

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Understands the principles of artistic creation and basic design and applies the art and design objects he creates within this framework.
2) Conducts the multifaceted research required for textile and fashion design processes and analyzes and interprets the results.
3) Creates original and applicable fabric, clothing and pattern designs by using elements from different historical periods and cultures in accordance with his purpose.
4) Recognizes textile raw materials and equipments.
5) Uses computer programs effectively in the garment and fabric surface design process.
6) Has professional technical knowledge regarding the implementation of clothing designs and production; In this context, recognizes and uses technological tools and equipment.
7) Understands the importance of interdisciplinary interaction and communication in textile and clothing design-production-presentation processes and reflects this on the processes.
8) Works in a programmed and disciplined manner in professional practices.
9) Realizes the necessity of lifelong learning to maintain his productivity, creativity and professional competence.
10) Understands, adopts and applies ethical responsibilities in professional practices; Has knowledge of relevant legal regulations.
11) Establishes effective visual, written and verbal communication in the field of textile and fashion design.
12) Reflects his knowledge on current and contemporary issues from all fields to his professional theoretical and practical studies on textile and clothing design; Understands the social and universal effects of these issues.
13) Has sufficient awareness about social justice, environmental awareness, quality culture and protection of cultural values.