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MATH 220Matrices

2-3 credits · Mathematics · Penn State

Systems of linear equations; matrix algebra; eigenvalues and eigenvectors; linear systems of differential equations. MATH 220 Matrices (2-3) (GQ) (BA) This course meets the Bachelor of Arts degree requirements.Systems of linear equations appear everywhere in mathematics and its applications. MATH 220 will give students the basic tools necessary to analyze and understand such systems. The initial portion of the course teaches the fundamentals of solving linear systems. This requires the language and notation of matrices and fundamental techniques for working with matrices such as row and column operations, echelon form, and invertibility. The determinant of a matrix is also introduced; it gives a test for invertibility. In the second part of the course the key ideas of eigenvector and eigenvalue are developed. These allow one to analyze a complicated matrix problem into simpler components and appear in many disguises in physical problems. The course also introduces the concept of a vector space, a crucial element in future linear algebra courses. This course is completed by a wide variety of students across the university, including students majoring in engineering programs, the sciences, and mathematics. (In case of many of these students, MATH 220 is a required course in their degree program.)

Before you enroll

Prerequisites

From the catalog: “MATH 110 or MATH 140 or MATH 140B or MATH 140E or MATH 140G or MATH 140H”

Counts toward

General education

Quantification (GQ)

Where it fits

Where it sits in degree plans

Suggested plans most often put it in Year 2 · Fall (24 programs).

Required in (38)

  • Aerospace Engineering, B.S.
  • Architectural Engineering, B.A.E.
  • Civil Engineering, B.S. (Capital)
  • Civil Engineering, B.S. (Engineering)
  • Computer Engineering, B.S. (Behrend)
  • Computer Engineering, B.S. (Engineering)
  • Computer Science, B.S. (Abington)
  • Computer Science, B.S. (Behrend)
  • Computer Science, B.S. (Capital)
  • Data Sciences, B.S. (Abington)
  • Data Sciences, B.S. (Engineering)
  • Data Sciences, B.S. (Information Sciences and Technology)
  • and 26 more

One of the options in (7)

  • Computer Science, B.S. (Engineering)
  • Electrical Engineering Technology, B.S. (Capital)
  • Electrical Engineering Technology, B.S. (Engineering)
  • Geophysics, Minor
  • Mathematics Applications, Minor
  • Mathematics, Minor (Science)
  • Mining Engineering, B.S.
What it opens up

Courses that list MATH 220 as a prerequisite (61)

  • A-I 305 Algorithmic Foundations for Artificial Intelligence
  • AERSP 301 Aerospace Structures
  • AERSP 309 Astronautics
  • AERSP 311 Aerodynamics I
  • AERSP 313 Aerospace Analysis
  • AERSP 424 Advanced Computer Programming
  • AERSP 462 Aerospace Autonomy
  • AIE 355 Optimization for Machine Learning
  • CE 404 Probabilistic Modeling and Machine Learning for Civil and Environmental Engineering
  • CMPEN 415 Computing with Commercial Quantum Computers
  • CMPEN 454 Fundamentals of Computer Vision
  • CMPSC 200 Programming for Engineers with MATLAB
  • CMPSC 445 Applied Machine Learning in Data Science
  • CMPSC 446 Data Mining
  • CMPSC 449 Foundations of Natural Language Processing
  • CMPSC 450 Concurrent Scientific Programming
  • CMPSC 455 Introduction to Numerical Analysis I
  • CMPSC 457 Computer Graphics Algorithms
  • CMPSC 458 Fundamentals of Computer Graphics
  • CMPSC 466 Introduction to Quantum Computation
  • CMPSC 489 Deep Learning for Computer Vision
  • DS 310 Machine Learning for Data Analytics
  • EE 337 Introduction to Quantum Information Science and Engineering
  • EE 350 Continuous-Time Linear Systems
  • EE 380 Introduction to Linear Control Systems
  • EE 415 Computing with Commercial Quantum Computers
  • EE 454 Fundamentals of Computer Vision
  • EE 456 Introduction to Neural Networks
  • EET 456 Automation and Robotics
  • EGEE 456 Introduction to Neural Networks
  • ESC 337 Introduction to Quantum Information Science and Engineering
  • ESC 407 Computer Methods in Engineering Science, Honors
  • ESC 456 Introduction to Neural Networks
  • IE 305 Product Design, Specification and Measurement
  • IE 405 Deterministic Models in Operations Research
  • IE 424 Process Quality Engineering
  • IE 425 Stochastic Models in Operations Research
  • IE 466 Concurrent Engineering
  • MATH 251H Honors Ordinary and Partial Differential Equations
  • MATH 310 Elementary Combinatorics
  • MATH 417 Qualitative Theory of Differential Equations
  • MATH 425 Introduction to Operations Research
  • MATH 430 Linear Algebra and Discrete Models I
  • MATH 441 Matrix Algebra
  • MATH 452 Deep Learning Algorithms and Analysis
  • MATH 455 Introduction to Numerical Analysis I
  • MATH 482 Mathematical Methods of Operations Research
  • MATH 484 Linear Programs and Related Problems
  • MATH 486 Mathematical Theory of Games
  • MATH 490H Honors Student Colloquium
  • ME 349 Intermediate Mechanics of Materials
  • ME 370 Vibration of Mechanical Systems
  • ME 410 Heat Transfer
  • ME 444 Engineering Optimization
  • PHYS 230 Introduction to Relativity
  • PHYS 337 Introduction to Quantum Information Science and Engineering
  • STAT 400 Statistical Modeling II
  • STAT 440 Computational Statistics
  • SUR 341 Adjustment Computations
  • SUR 421 Advanced Photogrammetry
  • SUR 422 Digital Photogrammetry