Akademik Dersler - Tanıtım


Code - Course Title	YZM3003 - Applied Artificial Intelligence
Course Type	Required Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+2
ECTS	6.0
Course Instructor(s)	DOKTOR ÖĞRETİM ÜYESİ NİHAL İNCE
Mode of Delivery	This course is offered exclusively in an in-person format.
Prerequisites	There are no prerequisites or co-requisites for this course.
Courses Recomended	There are no other recommended courses related to this one.
Required or Recommended Resources	Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson. Geron, A. (2022). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (3rd ed.). O\'Reilly Media. Jurafsky, D., & Martin, J. H. (2024). Speech and Language Processing (3rd ed. draft).
Recommended Reading List	Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson. Geron, A. (2022). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (3rd ed.). O\'Reilly Media. Jurafsky, D., & Martin, J. H. (2024). Speech and Language Processing (3rd ed. draft).
Assessment methods and criteria	1 midterm, 1 project, 1 final exam
Work Placement	This is not suitable for this class.
Sustainability Development Goals

Weeks	Topics
Week - 1	Intro to Applied AI: Project Lifecycle. Review of the Toolkit.
Week - 2	Search and Games. Coding a game with A* or Minimax.
Week - 3	Natural Language Processing (NLP) I - Basic Operations. NLTK library. Text Cleaning, Tokenization, Stopwords.
Week - 4	Text Vectorization. Bag-of-Words (BoW) and TF-IDF.
Week - 5	Text Classification with Classic ML (Spam Detection).
Week - 6	Computer Vision (CV) - Basic Operations. OpenCV library. Image reading/writing, basic filters.
Week - 7	Feature Extraction (HOG/SIFT) + Classification with Classic ML (SVM).
Week - 8	Project Development - Milestone I.
Week - 9	Image Classification with Deep Learning. Transfer Learning.
Week - 10	Text Classification with Deep Learning. RNN/LSTM implementation.
Week - 11	Reinforcement Learning (RL) - Core Concepts (Agent, Environment, Reward, Policy).
Week - 12	The Q-Learning Algorithm.
Week - 13	Project Development - Milestone II. Intro to MLOps (Model Deployment).
Week - 14	Final Project Presentations and Evaluation.

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
Toplam (%)		0