Akademik Dersler - Tanıtım

Last Updated: 23/06/2026

Code - Course Title	Course Type	Laboratory + Practice	ECTS
BVA226 - Data Analytics with Generative AI	IV. SEMESTER	2 +2	4.0

Language of Instruction	Türkçe
Course Type	Area Elective Courses
Course Instructor(s)	ÖĞR. GÖR. AHMET MÜCAHİD ARVASİ
Mode of Delivery	Face to face
Place of Delivery
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Prerequisites	There are no prerequisites or corequisites for this course.
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Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Introduction to Generative AI: Basic Concepts and Its Role in Data Analytics Processes
Week - 2		Data Preparation 1: Automated Data Cleaning and Missing Data Imputation with Generative AI
Week - 3		Data Preparation 2: Synthetic Data Generation Using GANs and Diffusion Models
Week - 4		Exploratory Data Analysis (EDA): Statistical Summarization of Datasets with AI Assistants
Week - 5		Automated Data Visualization: Dynamic Charts and Anomaly Detection via LLMs
Week - 6		Text Data Analysis 1: Processing Unstructured Data and Information Extraction
Week - 7		Text Data Analysis 2: Advanced Sentiment Analysis and Text Mining with LLMs
Week - 8		Midterm Exam
Week - 9		Predictive Modeling: Time Series Analysis and Trend Forecasting
Week - 10		Scenario-Based Simulations: "What-If" Analyses with Generative Models
Week - 11		Large Language Model Applications 1: Natural Language Querying for SQL and NoSQL Databases (Text-to-SQL)
Week - 12		Large Language Model Applications 2: Automated Reporting from Analytical Results and Interactive Data Dashboards
Week - 13		Ethics in Analytical Processes: Data Privacy (Anonymization of Personal Data) and Trustworthy AI
Week - 14		Algorithmic Bias Management and End-of-Term Project Presentations

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Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
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