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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. Vocational School of Information Technologies
  2. Department of Statistics
  3. Program in Big Data Analyst
  4. Course Structure Diagram with Credits
  5. Mathematics
  6. Description
  • Description
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Last Updated: 14/10/2026

Code - Course Title Course Type Laboratory + Practice ECTS
MAT841 - Mathematics I. SEMESTER 3 +0 5.0
Language of Instruction Türkçe
Course Type Required Courses
Course Instructor(s) ÖĞR. GÖR. HÜSEYİN REHA AKGÜN
Mode of Delivery face to face
Place of Delivery On Campus
Used Educational Platforms Face-to-face
Prerequisites Basic mathematical knowledge
Courses Recomended Algebra
Recommended Resources Generally accepted sources regarding Basic Mathematical Knowledge and Algebra
Work Placement NA
Aims of the Course To provide the mathematical and algorithmic logic underlying the processes of structuring, resizing, filtering, and optimizing data encountered daily when working with Python (Pandas/NumPy), SQL, and Machine Learning libraries.

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Powers and Roots, Absolute Value Lecture
Week - 2 Algebraic Expressions (Identities, Equations, Inequalities) Lecture
Week - 3 Introduction to Functions and the Coordinate Plane Lecture
Week - 4 Linear Modeling and Parabolas Lecture
Week - 5 Optimization (Linear Programming) Lecture
Week - 6 Logarithmic Transformations and Systems Lecture
Week - 7 Midterm Exam
Week - 8 The Concept of Matrices and Data Dimensions, Tensors Lecture
Week - 9 Basic Operations in Matrices Lecture
Week - 10 Scalar Product and Inner Product Lecture
Week - 11 Vector Distance and Algorithms Lecture
Week - 12 Matrix Multiplication and Inverse Matrix Lecture
Week - 13 Visualization of Matrices (Heat Maps) Lecture
Week - 14 Final Exam

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