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MATH 223

Linear Algebra I

Solving systems of linear equations. Vector spaces and linear transformations. Bases, matrix representations and coordinate transformations. Rank-Nullity Formula. Cayley-Hamilton Theorem. Eigenspaces and generalized eigenspaces. Determinants. Jordan canonical forms.

Credit3
ECTS5
BölümMathematics
FacultyFaculty of Science
MüfredatY2 Güz

Hocalar 0 bu dönem · 13 geçmiş

Geçmişte ders veren (13 kişi)
Müfit Sezer, Ahmet Muhtar Güloğlu, Özgün Ünlü, Ergün Yalçın, Bülent Ünal, Hamza Yeşilyurt, Alexandre Klyachko, Hakkı Turgay Kaptanoğlu, Nadia Romero Romero, Aslı Güçlükan İlhan, Laurence John Barker, İbrahim Dibağ, Simon Thomas

→ STARS müfredatı / syllabus

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Geçmiş GPA dağılımı 19 dönem · ort. 2.11

DönemCourse CPA
2025-2026 Fall 2.26 1 sec · 50 öğr
2024-2025 Fall 2.51 1 sec · 51 öğr
2023-2024 Fall 2.27 1 sec · 35 öğr
2022-2023 Fall 2.18 1 sec · 44 öğr
2021-2022 Fall 2.30 1 sec · 39 öğr
2020-2021 Fall 1.67 1 sec · 54 öğr
2019-2020 Fall 1.12 1 sec · 38 öğr
2018-2019 Fall 2.86 1 sec · 29 öğr
2017-2018 Fall 2.29 1 sec · 34 öğr
2016-2017 Fall 2.37 1 sec · 38 öğr

Aggregate course GPA — Bilkent STARS'tan public data. Hoca-bazlı per-section detayı için STARS evaluation report →. Öğrenci anket cevapları KVKK kapsamında defter'de tutulmaz.

Müfredat detayı STARS syllabus

📚 Önerilen kaynaklar

  • Zorunlu Elementary Linear Algebra with Applications B. Kolman and D. Hill · 2014 · 9th Edition
  • Önerilen Linear algebra K. Hoffman and R. Kunze · 1971 · Prentice Hall

⚖️ Değerlendirme

  • 60% — Midterm:Essay/written: Midterm Exams (×2)
  • 30% — Final:Essay/written: Final Exam (×1)
  • 0% — Quiz: (×1)
  • 10% — Homework: Homework (×4)

⚠️ FZ engelleyen şartlar

If the average of your midterm exams or your quiz average is below 20%, or your attendance is below 50%, then you will receive an FZ grade, and will not be able to take the final exam.

📅 Haftalık müfredat

Systems of linear equations, matrices (1.1-1.5) Echelon form of a matrix, Nonsingular matrices (2.1-2.3) Elementary matrices (2.3-2.4) Definition of determinant (6.1-6.2) Cofactor expansion and Adjoint formula (6.3-6.4) Vector spaces, Subspaces (3.1-3.4) Linear independence (3.5) Basis and dimension (3.6) Change of basis, Rank of a matrix (3.7-3.9) Linear transformations (5.1-5.2) Matrix of linear transformations (5.3) Eigenvalues and eigenvectors (7.1) Diagonalization (7.2) 7.3 Diagonalization of Symmetric Matrices ECTS - Workload Table: Activities Number Hours Workload Individual or group work 14 2 28 Midterm exam 2 2 4 Homework 10 1 10 Preparation for Final exam 1 20 20 Final exam 1 2 2 Course hours 14 3 42 Preparation for Midterm exam 2 15 30 Preparation for Quiz 10 1 10 Quiz 10 ,4 4 Total Workload: 150 Total Workload / 30: 150 / 30 5 ECTS Credits of the Course: 5 Type of Course: Lecture Course Material: See the recommended books Teaching Methods: Lecturing