Design and Analysis of Algorithms
Fall 2020
Lectures and Labs:
Lectures: Sunday from 11:30 to 1:45 pm in room 1125
Programming Lab: Thursday from 9:00 am to 3:00 pm in lab 1138
Office Hours: Sunday and Monday from 9:00 am to 11:00 am
Announcements:
HW#1 is posted on 4/11/2020 due day on 14/11/2020
HW#2 is posted on 22/02/2017 due day on 02/03/2017
Quiz#1 will be 08/03/2017 in class
HW#3 is posted on 27/02/2017 due day on 08/03/2017
grades of hw#1 and hw#2 are posted
HW#4 is posted on 06/03/2017 due day on 15/03/2017
HW#5 is posted on 14/03/2017 due day on 29/03/2017
Midterm exam will be on 05/04/2017
class slides are posted
HW#6 is posted on 23/03/2017 (not graded) due day on 04/04/2017
Review questions for the midterm exam are posted on 25/03/2017
Instructor:
Dr. Salah Aly Ahmed Email: salahuqu@gmail.com
Grading Policy:
70 points for final exam
60 points for assignments, project, midterm exam, attendance
20 points for final exam lab
No homework submissions will be accepted after due days
Text Book:
Introduction to Algorithms, 3rd edition by Cormen, Leiserson, Rivest, and Stein, 2009. PDF free copy
Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne
Lectures and handout notes.
Class Project:
Students are required to submitted a project regarding any topic related to design and analysis of algorithms. Each group consists of up to 4 students.
All projects will be discussed and evaluated on the last week of this class.
Collaboration policy for written assignments:
You are allowed to discuss assignment solutions to problems in groups of three, documenting who you discussed with at the top of your homework. You are not allowed to write up the solutions together. You must do that by yourself either by hand or computerized. Any duplicate solutions will be discarded.
List of Lectures: videos, slides, and implementations
Other Materials & Links:
Analysis of Algorithms page at Purdue
Algorithms for Modern Data Models: Ashish Goel (Stanford).
Algorithmic Techniques for Massive Data: Alexandr Andoni (Columbia).
Algorithms for Big Data: Chandra Chekuri (UIUC).
Algorithms for Big Data: Grigory Yaroslavtsev (UPenn).
Algorithms & Competitions