Students should consult the forum
at least once a week.
If you have a question, please check first the
policies
and the
forum
to see if your question is already answered. Email me if it isn't. I will only respond to emails sent to csc373 ☛ cs ☀ toronto ☀ edu .
You can also post non-personal questions (e.g. clarification requests about assignments,
explanation requests for topics covered in lectures, etc.)
on the
forum so other students can also benefit from them.
Course Info
Instructor
Name: Lalla Mouatadid
Email: csc373 ☛ cs ☀ toronto ☀ edu
Office: SF4301D
Teaching Assistants
Names: Robert Robere, Ladislav Rampasek, Jaiganesh Balasundaram
Lectures
When: Tuesday 6PM-8PM and Thursday 6PM-7PM
Where: BA 1180
Tutorials
When: Thursday 7PM-8PM
Where: BA 1180
Office Hours
Thursdays from 5-6PM in my office and 8-9PM in class (after the tutorial)
Course Website
http://www.cs.toronto.edu/~lalla/373s14/
Markus
Markus for CSC373H
Course Forum
Piazza forum for CSC373H
We will be monitoring the board regularly to answer your questions.
Textbook
[CLRS] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, "Introduction to Algorithms"
3rd. ed., 2009. Errata.
You have online access to the 2nd. edition through the UofT library.
Supplementary/Reference Book
[DPV] Sanjoy Dasgupta, Christos H. Papadimitriou, and Umesh Vazirani, "Algorithms", 2006. Errata
[JeffE] Jeff Erickson, "Algorithms Course Materials", 2011.
You can download the complete version free of charge.
Other Books
[GT] Michael T. Goodrich and Roberto Tamassia, Algorithm Design, Foundations, Analysis, and Internet Examples,
2001.
[KT] Jon Kleinberg and Éva Tardos,
"Algorithm Design", 2005.
[Skiena] Steven S. Skiena, "The Algorithm Design Manual", 2008.
[TAOCP] Donald E. Knuth, "The Art of Computer Programming", 1997-∞.
Course Description
Standard algorithm design techniques:
divide-and-conquer, greedy strategies, dynamic programming, linear programming, randomization, network flows, approximation algorithms.
Brief introduction to NP-completeness: polynomial time reductions, examples of various NP-complete problems, self-reducibility.
Students will be expected to show good design principles and adequate skills at reasoning about the correctness and complexity of algorithms.
(from Faculty of Arts & Science Calender)
Tentative Course Outline
Introduction (1 week),
Greedy Algorithms (2 weeks),
Dynamic Programming (2 weeks),
Network Flow (2 weeks),
Linear Programming (2 weeks),
NP-completeness (3 weeks),
Coping with Hard Problems (1 weeks).
Prerequisites
CSC263H1/CSC265H1,
CGPA 3.0 or enrolment in a CSC Subject POSt.
The prerequisite requirement is strictly enforced in this course.
Exclusion
CSC375H1/CSC364H1.
Breadth Requirement
The Physical and Mathematical Universes (5).
Marking Scheme
Title |
Points |
Notes |
Participation |
5 |
Actively engaging in lectures, tutorial attendance, picking up assignments and midterms |
Assignments |
40 |
Four assignments, each worth 10 points. |
Midterm |
15 |
One midterm worth 15 points. |
Final Exam |
40 |
To pass this course you must get at least 40% in the final exam. |
Total |
100 |
Course Information Sheet
Information Sheet