Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2021 287458 Computer Algorithms 1 3.0 3 ★ Po-Chun, Huang 訓四子三 56 1 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2021	287458	Computer Algorithms	1	3.0	3	★	Po-Chun, Huang	訓四子三	56	1

Course Plan：

Instructor Po-Chun, Huang

Email pchuang.19840320@gmail.com

Last Updated 2020-12-13 15:42:03

Course Objective This full-English course discusses the design and analysis of data structures and algorithms. The coverage of this graduate-level course is wider than the undergraduate-level course "Data Structures" and "Computer Algorithms", and includes the discussion of computation models, computation theories, and discrete mathematics techniques that assist the complexity analysis of data structures and algorithms. Advanced data structures and algorithms are covered; in addition, data structures and algorithms for novel computer hardware architecture (such as nonvolatile memories, distributed systems, and quantum computers) are also presented.

Course Schedule (Tentative!) 1. Mathematical background 1.1 Asymptotic growth rate of functions 1.2 Solving recurrence relations 1.3 Mathematical induction 2. Basic analysis techniques 2.1 Computational complexities -- lower bounds and upper bounds 2.2 Worst case analysis and average case analysis 2.3 Amortized analysis 3. Basic Design Paradigms 3.1 Divide and conquer 3.2 Greedy methods 3.3 Dynamic programming 3.4 Probabilistic algorithms 4. Computational Complexity 4.1 Information-theoretic arguments 4.2 Adversary arguments 4.3 Linear reduction of problems 4.4 NP-completeness

Evaluation and grading policy (Tentative!) In-class participation: 20% Homework assignments / in-class presentation: 25% Midterm examination: 25% Final examination: 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
(Tentative!) 1. Thomas H. Cormen et al., Introduction to Algorithms, 3rd Edition, MIT Press, 2009. 2. Peter Brass, Advanced Data Structures, Cambridge University Press, 2008. 3. Michael Sipser, Introduction to the Theory of. Computation, 3rd Edition, Cengage Learning, 2012.

The access to curricular consultation

The course corresponds to the SDGs

Does the course incorporate AI

Note
　

Instructor	Po-Chun, Huang
Email	pchuang.19840320@gmail.com
Last Updated	2020-12-13 15:42:03
Course Objective	This full-English course discusses the design and analysis of data structures and algorithms. The coverage of this graduate-level course is wider than the undergraduate-level course "Data Structures" and "Computer Algorithms", and includes the discussion of computation models, computation theories, and discrete mathematics techniques that assist the complexity analysis of data structures and algorithms. Advanced data structures and algorithms are covered; in addition, data structures and algorithms for novel computer hardware architecture (such as nonvolatile memories, distributed systems, and quantum computers) are also presented.
Course Schedule	(Tentative!) 1. Mathematical background 1.1 Asymptotic growth rate of functions 1.2 Solving recurrence relations 1.3 Mathematical induction 2. Basic analysis techniques 2.1 Computational complexities -- lower bounds and upper bounds 2.2 Worst case analysis and average case analysis 2.3 Amortized analysis 3. Basic Design Paradigms 3.1 Divide and conquer 3.2 Greedy methods 3.3 Dynamic programming 3.4 Probabilistic algorithms 4. Computational Complexity 4.1 Information-theoretic arguments 4.2 Adversary arguments 4.3 Linear reduction of problems 4.4 NP-completeness
Evaluation and grading policy	(Tentative!) In-class participation: 20% Homework assignments / in-class presentation: 25% Midterm examination: 25% Final examination: 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes (Tentative!) 1. Thomas H. Cormen et al., Introduction to Algorithms, 3rd Edition, MIT Press, 2009. 2. Peter Brass, Advanced Data Structures, Cambridge University Press, 2008. 3. Michael Sipser, Introduction to the Theory of. Computation, 3rd Edition, Cengage Learning, 2012.
The access to curricular consultation
The course corresponds to the SDGs
Does the course incorporate AI
Note