VTU 2022 Scheme  ·  Degree  ·  CSE

Linear Algebra BCS405D

Module-wise notes, PYQs, and a built-in resource explorer — everything you need to crack BCS405D in one focused page.

Browse Resources
CodeBCS405D
Credits03
CIE / SEE50 / 50
TypeTheory
Exam3 Hours
Hours / Week2:2:0:0
Save
Last Updated:  15 March 2026

Module Overview

M1

Module 1 Overview

Introduction, Vector spaces, Subspaces, Linear Combinations, Linear Spans, row space and column space of a Matrix, Linear Dependence and Independence, Basis and Dimension, Coordinates.

(RBT Levels: L1, L2 and L3)

Teaching-Learning Process: Chalk and talk method / PowerPoint Presentation

M2

Module 2 Overview

Introduction, Linear Mappings, Geometric linear transformation of i2, Kernel and Image of a linear transformations, Rank-Nullity Theorem (No proof), Matrix representation of linear transformations, Singular and Non-singular linear transformations, Invertible linear transformations

(RBT Levels: L1, L2 and L3)

Teaching-Learning Process: Chalk and talk method / PowerPoint Presentation

M3

Module 3 Overview

Introduction, Polynomials of Matrices, Applications of Cayley-Hamilton Theorem, Eigen spaces of a linear transformation, Characteristic and Minimal Polynomials of Block Matrices, Jordan Canonical form.

(RBT Levels: L1, L2 and L3)

Teaching-Learning Process: Chalk and talk method / PowerPoint Presentation

M4

Module 4 Overview

Inner products, inner product spaces, length and orthogonality, orthogonal sets and Bases, projections, Gram-Schmidt process, QR-factorization, least squares problem and least square error.

(RBT Levels: L1, L2 and L3)

Teaching-Learning Process: Chalk and talk method / PowerPoint Presentation

M5

Module 5 Overview

Diagonalization and Orthogonal diagonalization of real symmetric matrices, quadratic forms and its classifications, Hessian Matrix, Method of steepest descent, Singular value decomposition. Dimensionality reduction - Principal component analysis.

(RBT Levels: L1, L2 and L3)

Teaching-Learning Process: Chalk and talk method / PowerPoint Presentation

Resource Explorer

Browse all BCS405D study materials — notes, PYQs, and revision resources. Navigate folders for module-wise content and preview files before downloading.

Model Paper
Folder
Notes1
Folder
Notes2
Folder
Notes3
Folder
Syllabus
Folder
Textbook
Folder

Recently Viewed

Open any file to see it here for quick access later.

Need another subject?

Jump to other 4th Semester subjects and complete your study session.

Frequently Asked Questions

What is BCS405D (Linear Algebra BCS405D)?

Linear Algebra BCS405D is a VTU course covered through module-wise syllabus, notes, and PYQ-driven exam practice available on this page.

How many credits is BCS405D?

Credits for BCS405D: 03.

Are notes and previous year question papers available for BCS405D?

Yes. You can access organized notes, PDFs, and PYQ material from the file explorer/resources section on this page.

How should I prepare Linear Algebra BCS405D for VTU exams?

Start with module summaries, solve recent PYQs unit-wise, and finish with complete paper practice under time constraints for SEE readiness.

Is this BCS405D page updated for current VTU scheme?

Yes, this page is maintained with current scheme-oriented materials and practical exam-focused resource curation.

Explore More VTU Notes

About Linear Algebra (BCS405D)

Linear Algebra (BCS405D) is a key subject in the VTU engineering scheme. This dedicated page provides organized modules, download resources, and syllabus reviews designed to help students master the course material and prepare effectively for Visvesvaraya Technological University semester-end examinations.

Success Strategy

Focus on numerical proofs and architectural flowcharts. Practicing the math-heavy derivations is key for scoring the full 20 marks in these modules.

📘 Detailed Syllabus & Topic Breakdown

Detailed Subject Overview

This course in Linear Algebra (BCS405D) introduces fundamental concepts and methods crucial for engineering students. The curriculum covers core theoretical concepts and applications, ensuring students develop strong problem-solving skills tailored to university standards.

The skills gained from this course are highly relevant to professional careers in tech and modern engineering domains, forming the foundation of practical problem-solving in the industry.

Module-by-Module Breakdown

Module 1
Essential

Master the Introduction, Vector spaces, Subspaces, Linear Combinations, Linear Spans, row space and column space of a Matrix, Linear Dependence and Independence,...

Key: Exam Priority Concept
Module 2
Math Heavy

Master the Introduction, Linear Mappings, Geometric linear transformation of i2, Kernel and Image of a linear transformations, Rank-Nullity Theorem (No proof), M...

Key: Exam Priority Concept
Module 3
Logic Core

Master the Introduction, Polynomials of Matrices, Applications of Cayley-Hamilton Theorem, Eigen spaces of a linear transformation, Characteristic and Minimal Po...

Key: Exam Priority Concept
Module 4
Exam Focus

Master the Inner products, inner product spaces, length and orthogonality, orthogonal sets and Bases, projections, Gram-Schmidt process, QR-factorization, least ...

Key: Exam Priority Concept
Module 5
High Weight

Master the Diagonalization and Orthogonal diagonalization of real symmetric matrices, quadratic forms and its classifications, Hessian Matrix, Method of steepest...

Key: Exam Priority Concept

Professional Career Relevance

This subject provides a strong foundation for various technical roles, emphasizing analytical thinking, system design, and the practical application of engineering principles in the modern industry. Mastering these concepts prepares you for high-demand roles in Data Science, System Architecture, and Technical Leadership in top-tier tech companies.

Was This Helpful?