MTH3320
Computational linear algebra
基本信息
| 学分 | 6 credit points |
|---|---|
| 开课学期 | First semester |
| 校区 | Malaysia |
| 考核构成 | Final assessment - Exam (3 hours and 10 minutes) — 50% Continuous assessment — 50% |
开课安排1 条
| 教学期 | 授课方式 | 状态 |
|---|---|---|
| First semester | Teaching activities are on-campus (ON-CAMPUS) | 开课 |
以上为该校区在官方资料中登记的全部开课安排，不是汇总。同一门课可能在多个 教学期开课，也可能不同教学期的授课方式不同。
课程简介
The overall aim of this unit is to study the numerical methods for matrix computations that lie at the core of a wide variety of large-scale computations and innovations in the sciences, engineering, technology and data science. You will receive an introduction to the mathematical theory of numerical methods for linear algebra (with derivations of the methods and some proofs). This will broadly include methods for solving linear systems of equations, least-squares problems, eigenvalue problems, and other matrix decompositions. Special attention will be paid to conditioning and stability, dense versus sparse problems, and direct versus iterative solution techniques. You will learn to implement the computational methods efficiently, and will learn how to thoroughly test their implementations for accuracy and performance. You will work on realistic matrix models for applications in a variety of fields. Applications may include, for example: computation of electrostatic potentials and heat conduction problems; eigenvalue problems for electronic structure calculation; ranking algorithms for webpages; algorithms for movie recommendation, classification of handwritten digits, and document clustering; and principal component analysis in data science.
以上为 Monash Handbook 的官方原文，版权属 Monash University，此处按本站要求转载并标注出处： 官方页面 ↗
学习成果5 条
官方原文（Learning outcomes），版权属 Monash University。
- ULO1 Explain the mathematical theory behind a selection of important numerical methods for linear algebra, including the derivation of the methods and the analysis of their properties.
- ULO2 Explain and apply notions of conditioning, stability, accuracy, convergence, convergence speed and computational cost.
- ULO3 Demonstrate proficiency in the main linear algebra algorithms for solving linear systems, least-squares problems, eigenvalue decompositions, and other matrix decompositions, and apply them to problems in science, engineering, technology and big data analytics.
- ULO4 Implement advanced computational linear algebra methods, and demonstrate the correctness and efficiency of the implementations in systematic computational tests.
- ULO5 Demonstrate advanced skills in the written and oral presentation of theoretical and applied computational linear algebra problems.
教学方式与预期工作量
预期工作量
• Three 1-hour seminars;
• One 2-hour applied class (in weeks 2-12) and
• 7 hours of independent study per week.
官方原文，版权属 Monash University。
先修 / 同修要求
官方资料未列出该课程的先修要求。
先修链路
官方资料未列出该课程的先修要求，因此没有链路可画。
属于这些学位1 个
这门课出现在下列学位的官方结构里。反过来说：如果你读的是这些学位之一，它大概率是要修的 （必修还是选修取决于它在 Part 里的位置，点进去看结构）。
数据来源
- 数据来源
- 官方网页
handbook.monash.edu ↗ - 抓取时间
- 2026-09-13
- 可信度
- 程序抓取，未人工核实
查看官方完整描述 ↗ — 事实性字段（代码、学分、教学期、授课方式、考核权重、先修/同修/互斥关系）与 课程简介、学习成果、教学方式、预期工作量均取自官方 Handbook； 正文版权属 Monash University，此处转载并逐处标注出处。
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