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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Faculty of Computer and Information Sciences
  2. Department of Data Science and Analytics (English)
  3. Course Structure Diagram with Credits
  4. Data Science and Statistics
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 30/09/2026

Code - Course Title Course Type Laboratory + Practice ECTS
VBA105 - Data Science and Statistics I. SEMESTER 3 +0 6.0
Language of Instruction İngilizce
Course Type Required Courses
Course Instructor(s) PROF. DR. FİKRET ER
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites
Courses Recomended
Recommended Resources
Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Role of statistics in data science
Week - 2 Fundamental statistical concepts
Week - 3 Data types and structures
Week - 4 Data collection methods
Week - 5 Measures of central tendency
Week - 6 Measures of dispersion
Week - 7 Population and sample relationships
Week - 8 Basic data visualization principles
Week - 9 Identifying anomalies in data
Week - 10 Exploratory visual analysis techniques
Week - 11 Advanced visual representations
Week - 12 Analytical Thinking fundamentals
Week - 13 Formulating data-driven questions
Week - 14 Interpreting statistical findings

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 30
Final Exam 1 60
Quiz 1 10
Toplam (%) 100

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