Akademik Dersler - Tanıtım


Code - Course Title	BBO106 - Data Science
Course Type	Required Courses
Language of Instruction	Türkçe
Laboratory + Practice	3+2
ECTS	5.0
Course Instructor(s)	ARAŞTIRMA GÖREVLİSİ DOKTOR TANSU TEMEL
Mode of Delivery	Face to face
Prerequisites	There are no prerequisites or co-requisites for this course.
Courses Recomended	No courses are suggested.
Required or Recommended Resources	No resources are recommended.
Recommended Reading List	There is no reading list.
Assessment methods and criteria	1 Midterm exam, 3 Quizzes, Application, 1 Final exam
Work Placement	Students are expected to do practical work during the practical hours of the course.
Sustainability Development Goals	Health and Quality of Life , Quality Education , Industry, Innovation and Infrastructure , Sustainable Cities and Communities , Climate Action

Weeks	Topics
Week - 1	Introduction to Data Science and Big Data
Week - 2	Programming for Data Processing and Analysis
Week - 3	Data Cleansing, Preparation and Visualization
Week - 4	Scalable Data Analysis: Theories and Tools
Week - 5	Machine Learning for Big Data
Week - 6	Distributed Systems and Parallel Processing
Week - 7	Big Data Frameworks like Hadoop and Spark
Week - 8	NoSQL Databases and Scalable Storage Solutions
Week - 9	Cloud Computing and Big Data
Week - 10	Data Lakes and Data Storage Architect
Week - 11	Data Security and Privacy
Week - 12	Performance and Optimization Techniques
Week - 13	Scalability Issues and Solutions
Week - 14	Project Presentations

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	25
Quiz	1	10
Final Exam	1	40
Practice	1	25
Toplam (%)		100