| Course code | ENGG1120 |
| Course title | Linear Algebra for Engineers 線性代數及其工程應用 |
| Course description | This course aims at introducing students to the fundamental concepts and methods in linear algebra, which are key to many fields of engineering. Topics include systems of linear equations, Gauss elimination, matrix factorization, matrices and their operations, determinants, eigenvalues and eigenvectors, diagonalization, vector space, the Gram-Schmidt process, and linear transformation. 本科教授線性代數的基本概念與方法，以及其在工程上的應用。內容包括：線性方程組、高斯消去法、矩陣分解、矩陣及其運算、行列式、特徵值及特徵向量、對角化、向量空間、格拉姆–施密特正交化和線性變換。 |
| Unit(s) | 3 |
| Course level | Undergraduate |
| Exclusion | ENGG1410 or ESTR1004 or 1005 or MATH1030 |
| Semester | 2 |
| Grading basis | Graded |
| Grade Descriptors | A/A-: EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions. B+/B/B-: GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered. C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems. D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems. F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course. |
| Learning outcomes | At the conclusion of the course, students should be able to 1. demonstrate knowledge and understanding of the basic elements of linear algebra 2. apply results and techniques from linear algebra to solve simple engineering problems |
| Assessment (for reference only) |
Essay test or exam：65% Homework or assignment：25% Others：10% |
| Recommended Reading List | 1. Erwin Kreyszig, Advanced Engineering Mathematics, Wiley, 10th Edition, 2011. 2. Bernard Kolman, David R.Hill, Introductory Linear Algebra, an Applied First Course, Pearson/Prentice Hall, 8th Edition, 2005. 3. Steven J. Leon, Linear Algebra with Applications, Pearson/Prentice Hall, 7th Edition, 2006. |
| CSCIN programme learning outcomes | Course mapping |
| Upon completion of their studies, students will be able to: | |
| 1. identify, formulate, and solve computer science problems (K/S); | |
| 2. design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs (K/S); |
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| 3. receive the broad education necessary to understand the impact of computer science solutions in a global and societal context (K/V); | |
| 4. communicate effectively (S/V); |
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| 5. succeed in research or industry related to computer science (K/S/V); | |
| 6. have solid knowledge in computer science and engineering, including programming and languages, algorithms, theory, databases, etc. (K/S); | |
| 7. integrate well into and contribute to the local society and the global community related to computer science (K/S/V); | |
| 8. practise high standard of professional ethics (V); | |
| 9. draw on and integrate knowledge from many related areas (K/S/V); |
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| Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes; T = Teach; P = Practice; M = Measured | |