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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. Applied Computing for Analytics
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 21/07/2026

Code - Course Title Course Type Laboratory + Practice ECTS
VBA201 - Applied Computing for Analytics III. SEMESTER 3 +1 6.0
Language of Instruction İngilizce
Course Type Required Courses
Course Instructor(s) ARAŞ. GÖR. DR. ÖNDER DORAK
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 R Fundamentals: Core data structures, vectors, matrices
Week - 2 Lists and advanced indexing techniques
Week - 3 Advanced R Programming: Functional programming paradigms
Week - 4 Utilizing the apply family
Week - 5 Writing custom functions
Week - 6 Environment management
Week - 7 Data Manipulation with Tidyverse: Data importing pipelines
Week - 8 Cleaning messy datasets
Week - 9 Merging relational data
Week - 10 Reshaping with tidyr
Week - 11 Package development: Building structured R packages
Week - 12 Writing documentation
Week - 13 Version control integration
Week - 14 Ensuring reproducible statistical workflows

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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