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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. Probability for Data Science
  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
VBA109 - Probability for Data Science I. SEMESTER 2 +0 4.0
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 None
Courses Recomended None
Recommended Resources
Work Placement None
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 History of Probability and Its Importance in Data Science
Week - 2 Probability Rules
Week - 3 Conditional Probability and the General Multiplication Rule
Week - 4 Simulating Probability Experiments
Week - 5 Bayes Theorem
Week - 6 Discrete Random Variables, Binomial Distribution
Week - 7 review of the first 6 weeks
Week - 8 The Poisson Probability Distribution
Week - 9 The Hypergeometric Probability Distribution
Week - 10 Continuous Random Variables, Uniform distribution
Week - 11 Normal distribution
Week - 12 Normal Distribution applications
Week - 13 Exponential Distribütion
Week - 14 Review of the course with exercises

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 40
Final Exam 1 60
Toplam (%) 100

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