NCHU Course Outline

Course Name	(中) 演算法(3338)
	(Eng.) Algorithms
Offering Dept	Department of Applied Mathematics (Data Science and Computing Program)
Course Type	Required			Credits	3	Teacher	TSAI, HUNG-HSU
Department	Department of Applied Mathematics (Data Science and Computing Program) / Undergraduate			Language	Chinese	英文/EMI		Semester	2025-SPRING
Course Description	1. Study design, analysis, correctness proof, and implementation of algorithms for solving problems by computers. 2. Learn strategies for solving problems, techniques for designing and analyzing algorithms, and details for efficient implementations of algorithms in computers.
Prerequisites								self-directed learning in the course	Y

Relevance of Course Objectives and Core Learning Outcomes(%)			Teaching and Assessment Methods for Course Objectives
Course Objectives	Competency Indicators	Ratio(%)	Teaching Methods	Assessment Methods
1.Formulate applications as problems solvable by computers. 2.Design efficient algorithms for solving problems. 3.Prove the correctness of an algorithm. 4.Analyze the time and space complexity of an algorithms. 5.Efficient implementations of algorithms as programs in computers.	1.Basic Knowledge in Mathematical Sciences 5.Professional Knowledge in Computer Science	20 80	Exercises Discussion Lecturing	Quiz Written Presentation Attendance Oral Presentation Assignment
Course Content and Homework/Schedule/Tests Schedule
Week Course Content Week 1 Introduction to algorithm (the role of algorithm in computing) Week 2 Complexity Analysis(1) Week 3 Complexity Analysis(2) Sorting and Divide-and-Conquer(1) Week 4 Sorting and Divide-and-Conquer(2) Week 5 Sorting(1) Week 6 Sorting(2) Week 7 Data structure (elementary data structure, hash table, binary search tree, B-tree, red-black tree)(1) Week 8 Data structure (elementary data structure, hash table, binary search tree, B-tree, red-black tree)(2) Week 9 midterm exam Week 10 Dynamic programming Week 11 Greedy algorithms Week 12 Graph Search and Connectivity Week 13 Minimum Spanning Trees-Greedy algorithms (1) Week 14 Minimum Spanning Trees-Greedy algorithms (2) Shortest Paths-Dynamic programming (1) Week 15 Shortest Paths-Dynamic programming (2) Week 16 final-term exam (or report) Week 17 Study NP-complete or or listening to speech/online lesson (self-learning) (assessment: report) Week 18 Study Genetic Algorithm or listening to speech/online lesson (self-learning) (assessment: Genetic Algorithm Programming or report)
Evaluation
midterm exam (or report) (30%), Final-term exam (or report) (45%), Participation/Homework (15%), NP-complete (self-learning)(5%), Genetic Algorithm (self-learning)(5%), Extra credits/Projects (10%)
Textbook & other References
教科書 1.Introduction to Algorithms, Third Edition,Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein. (開發代理) https://en.wikipedia.org/wiki/Introduction_to_Algorithms 2.Foundations of Algorithms, Fifth Edition, Richard Neapolitan, PhD. (開發代理) 參考書目 1. Algorithms, 4th Edition, Robert Sedgewick and Kevin Wayne. 2. 演算法(第五版)--使用C++虛擬碼,Foundations of Algorithms, Fifth Edition, 作者： Richard Neapolitan, 譯者：蔡宗翰, 2017 (碁峯資訊)
Teaching Aids & Teacher's Website
http://140.120.7.156:8888/ftpstore/course/Algorithm/algorithm.htm
Office Hours
(二)7-8
Sustainable Development Goals, SDGs(Link URL)
include experience courses：N

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Update Date, year/month/day：None	Printed Date, year/month/day：2025 / 5 / 10
The second-hand book website：http://www.myub.com.tw/