ESTR 1002 程式設計與解難 Problem Solving By Programming

 

Course Code	ESTR 1002 ESTR1002			科目名稱		Problem Solving By Programming 程式設計與解難
教員	Professor FU Chi Wing [官方介紹及學術著作]			學　　分		3學分
課程性質	工程系必修(ELITE Stream)			同科其他選擇
Workload	l   非PAPER類HOMEWORK l   FINAL EXAM l   Lab								好重	1
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									平均
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									極輕
評價教學內容	#1 "Basic" C programming, 教嘅內容真係好難同深入好多，完全唔可以同ENGG1110比，但係學多好多嘢，每個星期都會有Lab 同homework，功課可以無限次交，但係好難做到滿分，亦都可以做好耐。冇programming 底嘅會極辛苦，建議讀ENGG1110。
評價教員教學	#1風趣幽默，上堂唔會瞓着，時不時會比啲Tips
CUSIS科目資料	Description： This is a computer-programming course to equip students with software knowledge and skills to solve engineering problems. Students will learn fundamental programming concepts in C, such as data representation and variables, operators and expressions, flow-control statements, functions, arrays, structures, pointer basics, input/ output handling, etc. In addition to lectures and e-learning, students will work in labs to practise solving problems and complete an engineering software project. The course will cover various problem solving methods such as incremental development, divide-and-conquer, debugging technique, finite-state machine, etc. Through practices, students will acquire skills to define problems and specifications, to perform modelling and simulation, to develop software system prototypes, to carry out verification, validation, and performance analysis.   Learning Outcome： At the end of the course of studies, students are expected to acquire the ability to 1. understand basic structural programming constructs in building a working software; 2. apply computer programming to solve engineering problems; 3. model a system on a computer to meet specifications and performance goals.
其他資料	2023Sem1：學位50 |註冊 45|剩餘 5
同學推薦	高度推薦		推薦		1	有保留		極有保留

ESTR 1005 線性代數及其工程應用 Linear Algebra for Engineers

 

Course Code	ESTR 1005 ESTR1005			科目名稱		Linear Algebra for Engineers 線性代數及其工程應用
教員	Professor LONG Zhuoyu [官方介紹] [學術著作]			學　　分		3學分
課程性質	工程系必修			同科其他選擇
Workload	l   非PAPER類HOMEWORK l   TUTORIAL / PRESENTATION l   MIDTERM l   FINAL EXAM l   一個linear algebra應用的group project，sem尾present 15分鐘。每兩個禮拜交不加分、不交會扣分的project report，report可以亂寫的，篇幅不限								好重
									重	2
									平均
									輕
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評價教學內容	#1 會upload teaching video, Lecture不會上堂，用作小組討論每一個禮拜的assignment，星期三的tutorial 則會解答所有題目。然而assignment太深，每題都好似做analysis咁樣，學唔到野；考試難度則比普通班深少少，合理程度；project令我認識linear algebra有好多應用，但無助學習。除非你係nds，數學天才，否則一切建議自學，不要上堂，跟教科書自己做exercise就好。 #2 Syllabus和ENGG1120是一样的，反正是工院必修课谈不上太深。教学模式是flip classroom， 简单来说就是周四放recording到blackboard让周末看完，然后周一给一份作业让你课上就开始做（没错周一上课时间什么都不讲）周三再把作业讲了然后让你周日之前交上。每周作业奇难无比做到怀疑人生，但是奇葩在于由于是周日才交作业所以实在搞不懂就看老师题解照着做就好…… 第一周会让学生安排组group弄一个project在期末做pre，emmm个人感觉对理解线性代数没什么作用。 midterm和final出的都比ENGG1120简单得多得多得多，迷惑……
評價教員教學	#1 prof超級1999，手字好亂，聽到人躁。prof係Teaching video讀出版社ppt，毫無作用。 #2 无情的念ppt机器+Chinglish，我是内地人都受不了那个英语了真的……到最后我都直接找ppt过来看不听recording了 给龟手很松（唯一一个也是最大的推荐上这门课的理由）
CUSIS科目資料	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.   Learning Outcome： 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
其他資料	2021Sem2：學位 60|註冊 59|剩餘 1
同學推薦	高度推薦		推薦		1	有保留		極有保留			1

CSCI 3230/ESTR 3108 人工智能之基本原理 Fundamentals of AI

Course Code	CSCI 3230/ESTR 3108			科目名稱		人工智能之基本原理 Fundamentals of AI
教員	Professor LEUNG Kwong Sak [官方介紹] [學術著作]			學　　分		3學分
課程性質	Computer Science  Steam 1必修課程			同科其他選擇
Workload	l   非PAPER類功課 l   FINAL EXAM l   Lab *ESTR 3108 比 CSCI3230 多一份AI project, 其他所有野一樣. 呢份AI project 要自學好多野, e.g. tensorflow								好重
									重	1
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評價教學內容	#1 無midterm, 好容易唔主動去溫書。Lab有準備就唔難，最好識少少prolog。assignment好似唔會email通知，要定期上website check #2 AI有趣但範圍太廣, 唔好比題目吸引到。 #3 bore, ppt not deep enough. don't take this course unless your stream required to; U will need a GPU to finish final project [admin案：粗口已過濾]
評價教員教學	#1 落堂可以問佢野，前提係你知自己唔明啲咩 #2   ppt bad, too many words on the ppt; 最好要自己溫先明講咩 #3   lesson bore [admin案：粗口已過濾]
CUSIS科目資料	Description： Basic concepts and techniques of artificial intelligence. Knowledge representation: predicate logic and inference, semantic networks, scripts and frames, and object-oriented representation. Searching: such as A*, hill-climbing, minimax and alpha-beta pruning. Planning: the frame problem and the STRIPS formalism, representation schemes and planning strategies. Neural networks: learning algorithms, neural architecture and applications. Natural language processing. Knowledge acquisition and expert systems: properties, techniques and tools of expert systems. Learning Outcome： Students will be able to: 1.Use agents to model AI problems 2.Use search techniques such as A* to search for optimal solutions for AI problems and to play games. 3.Use various logics to represent knowledge and to do reasoning and build expert systems. 4.Use computer learning techniques to acquire real life knowledge in an appropriate representation model (e.g. decision tree and neural networks). 5.Derive learning rules from first principle. 6.Solve real life problems (e.g.classifications and prediction) by such models. 7.Estimate complexity of AI algorithms and prove theorems by contradiction and other techniques. 8.Use computer vison techniques such edge detection to extract features.
其他資料	Course Outline： https://drive.google.com/open?id=1mc71plMjbd8gQWKPs0ZKjgBz4rfoyXNY 過往註冊資料： 2017Sem1：學位 130|註冊 128|剩餘2 [CSCI] 2017Sem1：學位 32|註冊 32|剩餘0 [ESTR] 2018Sem1：學位 130|註冊 113|剩餘 17 [CSCI] 2018Sem1：學位 30|註冊 21|剩餘 9 [ESTR]
同學推薦	高度推薦		推薦			有保留	2	極有保留			1

CSCI3230