MATH 1554

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Revision as of 15:18, 13 June 2021 by Zxcv (talk | contribs) (Overhauled content section)

Content and Structure

Topic List

  1. Linear Systems and Transformations
    1. Systems of Linear Equations
    2. Row Reduction and Echelon Forms
    3. Vector Equations
    4. The Matrix Equation
    5. Solution Sets of Linear Systems
    6. Linear Independence
    7. Linear Transforms
  2. Matrices and the Matrix Inverse
    1. Matrix Operations
    2. Matrix Inverse
    3. Invertible Matrix Theorem
    4. Partitioned Matrices*
    5. LU Factorization
    6. Leontief Input-Output Model*
    7. Computer Graphics*
    8. Subspaces
    9. Dimension and Rank
  3. Determinants and Eigenvalues
    1. Determinants
    2. Volume and Linear Transforms*
    3. Markov Chains*
    4. Eigenvalues and Eigenvectors
    5. Characteristic Equation
    6. Diagonalization
    7. Complex Eigenvalues*
    8. Google PageRank*
  4. Orthogonality
    1. Inner Products
    2. Orthogonal Sets
    3. Orthogonal Projections
    4. The Gram-Schmidt Process
    5. Least-Squares
  5. Symmetric Matrices and Quadratic Forms
    1. Symmetric Matrices
    2. Quadratic Forms
    3. Constrained Optimization*
    4. Singular Value Decomposition (SVD)*

* Topic not covered in MATH 1553

Prerequisite Knowledge

Almost no prerequisite knowledge is required, apart from algebra and trigonometry.

Relation to the Overall Curriculum

MATH 1554 is generally taken by freshmen due to having almost no prerequisites.

Workload

Content in MATH 1554 is typically assessed through homework, quizzes, and exams. These tend to have a mix of questions on theory, usually given as true/false questions, and computation. While the course requires no formal proofs, the theoretical nature of the course can be challenging for first-year students who have never taken these types of classes before. Homework may not be overly time-consuming, but questions can often involve a bit of thinking.

Resources

Course Page

Course page

Topic List

MATH 1554 is basically just MATH 1553 but with an extra set of chapters (denoted with a *).

  1. Systems of Linear Equations
  2. Vectors in Rn
  3. Linear Independence and Transformations
  4. Matrix Algebra
  5. Subspaces in Rn
  6. Determinants
  7. Markov Chains (*)
  8. Eigenvalues and Eigenvectors
  9. Complex Eigenvalues (*)
  10. PageRank (*)
  11. Orthogonality
  12. Symmetric Matrices
  13. Quadratic Forms (*)
  14. Singular Value Decomposition (*)

How it fits in the curriculum

Linear Algebra doesn't use any calculus, making it different from intro courses such as MATH 1551 and MATH 1552. This does mean that you can take MATH 1554 without any calculus credit.

However, future calculus classes like Multivariable Calculus (MATH 2550/2551) and Differential Equations (MATH 2552) will use Linear Algebra concepts such as matrices, determinants, eigenvalues, characteristic equations, etc. Additionally, Linear Algebra is important for math classes required for CS such as Applied Combinatorics (MATH 3012) and Algorithms (CS 3510)

Current Registration Info

This is a linked course with both a lecture and studio section. You must register for a lecture section (e.g. A, B, C) and a corresponding studio section with the same letter (e.g. lecture section A will have studio section A01, A02, etc.).

For the lecture sections, notice how they all include one time-block very late in the day. This is likely the test period, which will only meet a few times per semester. [TODO some1 confirm]

Prerequisites

At least one of the following:

  • D or higher in MATH 1113 (Precalculus).
  • D or higher in MATH 1552 (Integral Calculus) or equivalent.
  • 620 or higher on the Math section of the SAT
  • 26 or higher on the Math section of the ACT.

Equivalent Courses

MATH 1564. If you enjoy theoretical math and proofs a lot, and consider yourself very good at math, consider taking MATH 1564 instead.

Majors That Require This Class

  • Applied Physics
  • Computational Media
  • Computer Engineering
  • Computer Science
  • Earth and Atmospheric Sciences
  • Electrical Engineering
  • Mathematics
  • Physics