This is a three-credit course where students learn algorithm definition; tools and methods for
algorithm analysis and design; mathematical notations; choice of data structure, space and time
efficiency, computational complexity, and algorithms for searching and sorting.
- Apply the mathematical notations used in the field of design & analysis of
- Apply the design & analysis of algorithms with illustrations from different problem
- Use the methods for analyzing and designing algorithms in the field of Computing
- Use graph algorithms.
- Search and sort advanced data structures.
- Review of Algorithm Analysis Chapter 1
- Basic Data Structures Chapter 2
- Search Trees and Skip Lists Chapter 3
- Sorting, Sets, and Selection Chapter 4
- Fundamental Techniques Chapter 5
- Graphs Chapter 6
- Weighted Graphs Chapter 7
- Network Flow Chapter 8
- Text Processing Chapter 9
Required text and materials
M.T. Goodrich & R. Tamassia. Algorithm Design: Foundations, Analysis, and Internet
Examples . (2). John Wiley & Sons, 2001.
Type: Textbook, ISBN: 978-0-471-38365- 9 /
Note: The final exam is an open book exam. However, no digital or electronic resources will be
Please be aware that due to COVID-19 safety guidelines all in-person exams have been suspended. As such, all final exams are currently being delivered through ProctorU, which has an approximate fee of $35 involved. There will be more information in your course shell, on how to apply, if your course has a final exam.
To successfully complete this course, students must achieve a passing grade of 50% or higher on
the overall course and 50% or higher on the Final mandatory exam.
|Final Exam *
Open Learning Faculty Member
An Open Learning Faculty Member is available to assist students. Primary communication is
through the Learning Environment's "Mail" tool or by phone. Students will receive the necessary
contact information at the start of the course.