MATH208 - Matrix Algebra with Applications
Course: MATH208 (Matrix Algebra with Applications) in MATH department at University of Washington.
Credit Hours: 4 • Academic Level: second-year undergraduate course
Course Requirements: No prerequisites required - suitable for beginning students
Future Opportunities: Unlocks 59 advanced courses for further study
Course Type: Foundation course - forms the base for multiple advanced topics
Part of the MATH curriculum at University of Washington, helping students progress through degree requirements.
Courses unlocked by MATH208
- ESS524 - Numerical Heat and Mass Flow Modeling in the Earth Sciences
- INDE310 - Linear and Network Programming
- MATH514 - Networks and Combinatorial Optimization
- STAT502 - Design and Analysis of Experiments
- CSE462 - Wireless Communication
- CSE586 - Introduction to Synthetic Biology
- ESS469 - Machine Learning in Geosciences
- EE418 - Network Security and Cryptography
- ECON580 - Econometrics I: Introduction to Mathematical Statistics
- CSE446 - Machine Learning
- CSE422 - Toolkit for Modern Algorithms
- AMATH481 - Scientific Computing
- AMATH483 - High-Performance Scientific Computing
- CSE438 - Computational Neuroscience
- CHEME512 - Methods of Engineering Analysis
- CSE478 - Autonomous Robotics
- CSE486 - Introduction to Synthetic Biology
- EE345 - Introduction to Foundations of Machine Learning
- EE447 - Control System Analysis I
- EE460 - Neural Engineering
- EE466 - Neural Computation and Engineering Laboratory
- EE528 - Quantum Optics for Quantum Information Applications
- ME373 - Introduction to System Dynamics
- ME478 - Finite Element Analysis
- ESS411 - Geophysical Continuum Mechanics
- ESS412 - Introduction to Seismology
- ESS414 - Geophysics: Fluids
- ESS511 - Geophysical Continuum Mechanics
- ESS512 - Seismology
- ESS514 - Geophysics: Fluids
- BIOEN420 - Medical Imaging
- BIOEN437 - Computational Systems Biology
- BIOEN451 - Optical Coherence Tomography
- BIOEN466 - Neural Computation and Engineering Laboratory
- STAT423 - Applied Regression and Analysis of Variance
- CHEME476 - Introduction to Synthetic Biology
- AA447 - Control in Aerospace Systems
- AMATH482 - Computational Methods for Data Analysis
- AMATH514 - Networks and Combinatorial Optimization
- BIOEN450 - Tissue Optics and Imaging
- BIOEN523 - Introduction to Synthetic Biology
- CEE415 - Machine Learning for Civil Engineers
- CFRM405 - Mathematical Methods for Quantitative Finance
- CET515 - Machine Learning for Civil Engineers
- CHEM464 - Computers in Data Acquisition and Analysis
- CSE434 - Introduction to Quantum Computation
- STAT441 - Multivariate Statistical Methods
- STAT509 - Econometrics I: Introduction to Mathematical Statistics
- AA528 - Spacecraft Dynamics and Control
- CHEME456 - Quantum Mechanics for Chemical Engineers
- CHEME576 - Introduction to Synthetic Biology
- EE347 - Introduction to Robotics and Control Systems
- EE423 - Introduction to Synthetic Biology
- EE445 - Fundamentals of Optimization and Machine Learning
- EE467 - Machine Learning for Cybersecurity
- EE523 - Introduction to Synthetic Biology
- MOLENG525 - Introduction to Synthetic Biology
- BIOEN423 - Introduction to Synthetic Biology
- BIOEN460 - Neural Engineering
Academic Planning at University of Washington
Students planning MATH208 at University of Washington should complete 0 prerequisites before enrollment.
Future Pathways: Completing MATH208 enables enrollment in 59 advanced courses for further study
This second-year course at University of Washington integrates into structured degree pathways for MATH programs, supporting timely graduation and academic progression.