Linear Algebra
General
Code: BSC_IT2
Language: English
Delivery: In person
Prerequisites: None
Workload
- Lectures: 39.0 hours
- Lab: 0.0 hours
- Study: 98.0 hours
- Project: 13.0 hours
Course Content
Week 1: Introduction to linear algebra, vectors and geometry
Week 2: Matrices and matrix operations
Week 3: Systems of linear equations
Week 4: Solution methods (Gaussian elimination)
Week 5: Determinants
Week 6: Matrix inverse and applications
Week 7: Vector spaces and subspaces
Week 8: Basis and dimension
Week 9: Linear transformations
Week 10: Eigenvalues and eigenvectors
Week 11: Diagonalization
Week 12: Applications in IT (ML, graphics, PCA) & review
Learning Outcomes
Upon successful completion of the course, students will be able to:
Understand fundamental concepts of linear algebra (vectors, matrices, spaces)
Solve systems of linear equations using analytical and computational methods
Perform matrix operations and understand their properties
Compute determinants and matrix inverses
Analyze vector spaces and subspaces
Compute eigenvalues and eigenvectors
Apply linear algebra in IT domains (machine learning, graphics, data science)
Use software tools for linear algebra computations
Develop mathematical reasoning and problem-solving skills
Skills
The course fosters the following competences:
Search for, analysis and synthesis of data and information, with the use of the necessary technology
Adapting to new situations
Decision-making
Working independently
Team work
Working in an international environment
Working in an interdisciplinary environment
Production of new research ideas
Project planning and management
Respect for difference and multiculturalism
Respect for the natural environment
Showing social, professional and ethical responsibility and sensitivity to gender issues
Criticism and self-criticism
Production of free, creative and inductive thinking
Others:
Mathematical modeling of IT problems
Algorithmic and analytical thinking
Familiarity with computational tools (Python, MATLAB)