查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

109-2 283000 計算機演算法 1 3.0 3 ★ 蕭榮修資工三 64 8 資工三與電資二合開

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
109-2	283000	計算機演算法	1	3.0	3	★	蕭榮修	資工三	64	8	資工三與電資二合開

教學大綱與進度：

教師姓名蕭榮修

Email rshsiao@ntut.edu.tw

最後更新時間 2020-12-12 17:38:13

課程大綱介紹計算機演算法的設計與分析,內容包含了: 函數成長, 遞迴關係, 排序及序列統計, 基礎與進階資料結構, 動態規劃, 貪婪演算法, 搜尋, 圖形與幾何演算法, 字串比對, NP-completeness, 近似演算法, 及平行與分散式演算法. This course gives a broad introduction about the design and analysis of computer algorithms. General topics to be covered include: growth of functions, recurrences, sorting and order statistics, fundamental and advanced data structures, dynamic programming, greedy algorithms, searching, graph and geometry algorithms, string matching, NP-completeness, approximation algorithms, parallel and distributed algorithms.

課程進度 Calendar: 1. Mathematical Foundations: Introduction 2. Analyzing & Designing Algorithms 3. Growth of Functions 4. Recurrences 5. Heapsort 6. Quicksort 7. Sorting in Linear Time 8. Medians and Order Statistics 9. Mid-term Exam 10. Greedy Algorithms 11. Dynamic Programming_1 12. Dynamic Programming_2 13. Other Optimization Algorithms 14. Elementary Graph Algorithms 15. Minimum Spanning Trees 16. Shortest Paths Algorithms 17. NP-Completeness 18. Final Exam

評量方式與標準 Grading: 10% Attendance 20% Assignments 30% Mid-term Exam (take home 40%, in class 60%) 40% Final Exam (take home 40%, in class 60%)

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：是
1. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Second Ed., The MIT Press, 2001. (開發)

課程諮詢管道

備註

教師姓名	蕭榮修
Email	rshsiao@ntut.edu.tw
最後更新時間	2020-12-12 17:38:13
課程大綱	介紹計算機演算法的設計與分析,內容包含了: 函數成長, 遞迴關係, 排序及序列統計, 基礎與進階資料結構, 動態規劃, 貪婪演算法, 搜尋, 圖形與幾何演算法, 字串比對, NP-completeness, 近似演算法, 及平行與分散式演算法. This course gives a broad introduction about the design and analysis of computer algorithms. General topics to be covered include: growth of functions, recurrences, sorting and order statistics, fundamental and advanced data structures, dynamic programming, greedy algorithms, searching, graph and geometry algorithms, string matching, NP-completeness, approximation algorithms, parallel and distributed algorithms.
課程進度	Calendar: 1. Mathematical Foundations: Introduction 2. Analyzing & Designing Algorithms 3. Growth of Functions 4. Recurrences 5. Heapsort 6. Quicksort 7. Sorting in Linear Time 8. Medians and Order Statistics 9. Mid-term Exam 10. Greedy Algorithms 11. Dynamic Programming_1 12. Dynamic Programming_2 13. Other Optimization Algorithms 14. Elementary Graph Algorithms 15. Minimum Spanning Trees 16. Shortest Paths Algorithms 17. NP-Completeness 18. Final Exam
評量方式與標準	Grading: 10% Attendance 20% Assignments 30% Mid-term Exam (take home 40%, in class 60%) 40% Final Exam (take home 40%, in class 60%)
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：是 1. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Second Ed., The MIT Press, 2001. (開發)
課程諮詢管道
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