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