Course Outline Dr NGUYEN Ho Man Rang Outcome Distribution About this course Structure Contents Assessment References Methodology 0 1 Chapter 0 Course Outline Data Structures and Algorithms Dr NGUYEN H[.]
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Chapter 0
Course Outline
Data Structures and Algorithms
Dr NGUYEN Ho Man Rang Faculty of Computer Science and Engineering
Ho Chi Minh University of Technology, VNU-HCM
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About this course
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Assessment References Methodology
Overview
1 Outcome
Distribution
2 About this course
Structure
3 Contents
Assessment
References
Methodology
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Learning outcome
By completing this course, students are able to:
• USE fundamental data structures like list,
stack, queue, tree, graph, and hash table
for programming and particular problems
• EXPRESS algorithms using pseudocode as
well as using C++
• ANALYZE the computational complexity
of algorithms associated with these data
structures.
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Distribution
• Course credit: 4
• Lectures: 45 period units
• Tutorial + Lab: 30 period units
• Total: 75 period units
• Teaching from January 2019 to May 2019
• Final exam: in June 2019
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Structure
• Lectures: course contents in class
• Readings: course contents at home
• Tutorials: QAs and exercises
• Lab: coding practice
• Assignments: small projects
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Contents and Schedule
1 Intro & C++ Review
2 Complexity of Algorithms
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Labs Schedule
4 Recursion & C++ Review
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Assessment
• Quiz: 10%
• Lab: 10%
• Lab Exam: 5%
• Assignment: 25% (A1:5%, A2:10%,
A3:10%)
• Final Exam: 50% (Open book)
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References
1 "Data Structures and Algorithm Analysis" - Clifford
A Shaffer (Edition 3.2)
2 "Data Structures: a Pseudocode Approach with C++",
R.F.Gilberg and B.A Forouzan, Thomson Learning Inc.,
2001
3 "Data Structures and Algorithms in C++", A Drozdek,
Thomson Learning Inc., 2005
4 "C/C++: How to Program", 7th Ed – Paul Deitel and
Harvey Deitel, Prentice Hall, 2012
5 Internet
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Website
• Sakai portal
• https://elearning-cse.hcmut.edu.vn/portal
• BK E-learning
• http:
//e-learning.hcmut.edu.vn/login/index.php
• Any question:
• Email: nguyenhomanrang@hcmut.edu.vn
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Preparation for the course
• Materials:
• Slides of this course
• Ebook: Data Structures and Algorithm Analysis
-Clifford A Shaffer (Edition 3.2).
http://people.cs.vt.edu/~shaffer/Book/
• Tools:
• CodeBlocks (Cross-platform)
• Visual C++ Express (Windows)
• XCode (Mac OS)
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Methodology
• Outside of lecture room
• Read slides, books
• Do exercises, labs, assignments
• Check BK-Elearning and SAKAI
• During lectures:
• Listen & Discuss