Akademik Dersler - Tanıtım


Code - Course Title	İST257 - Introduction to Data Science
Course Type	Area Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	2+0
ECTS	3.0
Course Instructor(s)	DOKTOR ÖĞRETİM ÜYESİ İSMAİL YENİLMEZ
Mode of Delivery	The mode of delivery of this course is face to face.
Prerequisites	There is no recommended optional programme component for this course.
Courses Recomended	There is no recommended optional programme component for this course.
Recommended Reading List	Practical Statistics for Data Scientists by Peter Bruce & Andrew Bruce, O'Reilly; Python Data Science Handbook: Essential Tools for Working with Data by Jake VanderPlas, O'Reilly.
Assessment methods and criteria	1 Midterm Exam, 1 Homework and Final Exam (Classic)
Work Placement	Not suitable for this course.
Sustainability Development Goals

Weeks	Topics
Week - 1	Data Science
Week - 2	Statistics, Machine Learning, and Software for Data Science
Week - 3	Data Science Project and Data Science Experiment
Week - 4	The Need for Data Science: Organization Perspective
Week - 5	Data Scientist Skills
Week - 6	Data Science Team
Week - 7	Interdisciplinary Relation in Teams
Week - 8	Data Analysis
Week - 9	Descriptive Analysis
Week - 10	Inferential Analysis
Week - 11	Data Science in Real Life
Week - 12	Data Cleaning/Cleansing
Week - 13	Designing and Modelling
Week - 14	Scenario, Analysis, and Interpretation for Data

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
2.Midterm Exam	1	30
Homework	1	30
Final Exam	1	40
Toplam (%)		100