| Week |
Subject |
Related Preparation |
| 1) |
A Review of AI Concepts Rational Agents |
|
| 2) |
Solving Problems by searching - Search algorithms (Uninformed and Informed) |
|
| 3) |
Solving Problems by searching - Constraint Satisfaction Problems |
|
| 4) |
Games - Adversarial Search, Game theory |
Assignment #1 |
| 5) |
Logical agents - Propositional logic, First Order Logic and inference |
|
| 6) |
Planning |
|
| 7) |
Probabilistic Reasoning - Basic probability concepts, Bayesian inference |
Assignment #2 |
| 8) |
Probabilistic Reasoning - Naive Bayes models, Bayesian networks |
|
| 9) |
Machine Learning - Supervised vs. unsupervised learning, Decision trees, Nearest neighbor classifiers, Support Vector Machines |
Midterm Exam |
| 10) |
Neural Networks |
Assignment #3 |
| 11) |
Deep Learning - Convolutional Neural Networks |
|
| 12) |
Deep Learning |
Assignment #4 |
| 13) |
Reinforcement Learning - Markov decision processes, Q-learning |
|
| 14) |
AI, Ethics and Society |
|
| Course Notes / Textbooks: |
Stuart Russell, Peter Norvig, “Artificial Intelligence: A Modern Approach” (3rd Edition), Prentice Hall, ISBN-10: 0-13-604259-7, 2010.
Selected papers (an additional listing of literature will be provided based on the students’ projects) |
| References: |
Stuart Russell, Peter Norvig, “Artificial Intelligence: A Modern Approach” (3rd Edition), Prentice Hall, ISBN-10: 0-13-604259-7, 2010.
Selected papers (an additional listing of literature will be provided based on the students’ projects) |
| |
Program Outcomes |
Level of Contribution |
| 1) |
Build up a body of knowledge in mathematics, science and Artificial Intelligence Engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems. |
5 |
| 2) |
Design complex Artificial Intelligence systems, platforms, processes, devices or products under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. |
5 |
| 3) |
Identify, formulate, and solve complex Artificial Intelligence Engineering problems; select and apply proper modeling and analysis methods for this purpose. |
5 |
| 4) |
Devise, select, and use modern techniques and tools needed for solving complex problems in Artificial Intelligence Engineering practice; employ information technologies effectively. |
4 |
| 5) |
Design and conduct numerical or physical experiments, collect data, analyze and interpret results for investigating the complex problems specific to Artificial Intelligence Engineering. |
4 |
| 6) |
Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. Write and understand reports, prepare design and production reports, deliver effective presentations, give and receive clear and understandable instructions. |
3 |
| 7) |
Recognize the need for life-long learning; show ability to access information, to follow developments in science and technology, and to continuously educate oneself. |
3 |
| 8) |
Develop an awareness of professional and ethical responsibility, and behave accordingly. Be informed about the standards used in Artificial Intelligence Engineering applications. |
4 |
| 9) |
Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development. |
|
| 10) |
Acquire knowledge about the effects of practices of Artificial Intelligence Engineering on health, environment, security in universal and social scope, and the contemporary problems of Artificial Intelligence Engineering; is aware of the legal consequences of Mechatronics engineering solutions. |
|
| 11) |
Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Artificial Intelligence-related problems. |
|