Math 152 introduces linear systems with a computational focus, bridging pure mathematics and applied science. Unlike Math 111 (which emphasizes abstract linear algebra) or Math 131 (which is proof-based), Math 152 focuses on solving systems of linear equations, numerical methods, and applications to engineering, computer science, and the physical sciences. If you need linear algebra for practical problem-solving—not theoretical rigor—Math 152 is designed for you. It's particularly popular with engineering and computer science students who need matrix algebra for their disciplines.
What is covered in UBC Math 152?
Math 152 introduces linear systems with applications to science and engineering. Topics include:
- Systems of linear equations: Gaussian elimination, row reduction, and solution methods
- Matrices and operations: Matrix arithmetic, inverses, and special matrices (identity, diagonal, symmetric)
- Vector spaces and subspaces: Basic concepts without heavy abstraction
- Linear transformations: Matrix representations and applications
- Determinants: Calculation methods and applications to invertibility
- Eigenvalues and eigenvectors: Finding eigenvalues, diagonalization, and applications to systems of differential equations
- Orthogonality and least squares: Projections, orthogonal bases, and approximation methods
- Numerical methods: Iterative methods, error analysis, and computational techniques
- Applications: Systems of differential equations, Markov chains, and engineering problems
Math 152 is typically taken by engineering and computer science students as part of their required math sequence.
Common challenges students face in Math 152
Computational speed matters
Unlike theoretical courses, Math 152 exams are computation-heavy. You need to row-reduce matrices, find eigenvalues, and solve systems quickly and accurately—often under tight time constraints.
Applications require setup
Word problems ask you to model real-world scenarios as linear systems. Translating engineering or physics problems into matrix form requires careful reading and understanding of context.
Eigenvalues and diagonalization
This topic combines computation (finding eigenvalues) with conceptual understanding (diagonalizability). Many students struggle with the characteristic polynomial and eigenvector calculations.
Least squares and projections
These topics feel abstract compared to solving systems. Understanding why least squares works and how to apply it requires connecting geometry with matrix algebra.
How Learn4Less helps you succeed in Math 152
Our tutors understand both the computational techniques and the applied context of Math 152.
Efficient computation
We teach you fast, reliable methods for row reduction, finding determinants, and calculating eigenvalues. You'll learn shortcuts and strategies that save time on exams.
Application problem strategies
We walk you through how to read engineering or physics problems, identify the relevant variables, and set up matrix equations correctly.
Conceptual clarity
We help you understand the geometric meaning behind projections, least squares, and eigenvalues—so you're not just memorizing procedures.
Math 152 exam and midterm preparation
Math 152 typically has two midterms and a final exam, all computation-focused. Here's how we prepare you:
Speed drills
We practice row reduction, determinant calculations, and eigenvalue problems until they become automatic. Speed matters on Math 152 exams.
Past exam practice
We work through previous years' exams so you know what problem types to expect. You'll practice under realistic time constraints.
Eigenvalue mastery
Eigenvalues and diagonalization appear heavily on exams. We ensure you can find eigenvalues quickly, calculate eigenvectors correctly, and determine diagonalizability.
Why choose Learn4Less for Math 152 tutoring?
First-year specialization
We focus on UBC's first-year math courses, including linear systems. Our tutors have guided hundreds of Math 152 students successfully.
Experience with UBC curricula
We know UBC's Math 152 syllabus, typical textbooks, and exam formats. We tailor our sessions to what UBC professors emphasize.
Flexible formats
Choose in-person tutoring near UBC or online sessions with screen sharing. Need help before a specific midterm? Book a targeted prep session. Want ongoing support? Weekly tutoring keeps you on track.
Video study packages
Prefer self-paced learning? Our video packages cover key Math 152 topics—perfect for reviewing before exams.
Frequently Asked Questions
What's the difference between Math 152 and Math 111?
Math 152 focuses on computational methods and applications to engineering and computer science. Math 111 covers similar content but emphasizes abstract vector spaces and theoretical understanding. Check your program requirements to see which one you need.
Can I take Math 111 instead of Math 152?
Often, yes—check with your program. Math 111 is generally accepted as equivalent to Math 152, but Math 152's applied focus may be more relevant for engineering students.
Is Math 152 easier than Math 111?
They're differently challenging. Math 152 is more computational and less abstract, which some students find easier. But the exams require speed and accuracy, which can be demanding in its own way.
How much programming is in Math 152?
It depends on the instructor, but some sections incorporate MATLAB or Python for numerical methods. The focus is on understanding algorithms, not extensive coding.
When should I get a tutor for Math 152?
As soon as you feel slow with computations or struggle with applications. The course moves quickly, and falling behind on eigenvalues or diagonalization makes the second half of the course very difficult. Proactive tutoring helps you stay efficient and confident.