{"id":9,"title":"Algorithms","credit_hour":"4","lecture_hour":"60","outcome":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ul>\r\n<li>Students will learn methods for designing efficient algorithms, evaluating their performance, and ways of establishing precise limits on the possible effectiveness of classes of algorithms<\/li>\r\n<li>They will learn standard algorithms for fundamental problems.<\/li>\r\n<\/ul>\r\n<\/body>\r\n<\/html>","description":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<p>Techniques and principles of algorithms design including divide-and-conquer and greedy algorithms. Complexity (worst and average case) analysis and their associated asymptotic notations (Theta, Big O, Omega). Iterative sorting algorithms: Bubble sort, insertion sort. Recursive sorting: merge sort, quick sort, heap sort. Sorting in linear time: counting\/radix sort. Decision tree analysis: N*logN bound on comparison based sorting. Algorithms for graph problems: Shortest path (Dijkstra), minimum spanning trees (MST algorithms: Kruskal, Prim). Hashing. Discussion on NP-class problems (e.g. Travelling Salesman Problem).<\/p>\r\n<\/body>\r\n<\/html>","books":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ol>\r\n<li><a href=\"https:\/\/www.amazon.com\/Algorithms-4th-Robert-Sedgewick\/dp\/032157351X\" target=\"_blank\"><em>Algorithms<\/em> (4th Edition) by R. Sedgewick, K Wein<\/a><\/li>\r\n<li><a href=\"https:\/\/www.amazon.com\/Introduction-Algorithms-Second-Thomas-Cormen\/dp\/0262032937\" target=\"_blank\"><em>Introduction to Algorithms (2nd Edition)<\/em> by T. Cormen, C. Lieserson, R. Rivest, C. Stein<\/a><\/li>\r\n<li><a href=\"https:\/\/www.amazon.com\/Art-Computer-Programming-Vol-Fundamental\/dp\/0201896834\" target=\"_blank\"><em>Art of Computer Programming Vol. 1 (Fundamental Algorithms)<\/em> by D. Knuth<\/a><\/li>\r\n<\/ol>\r\n<\/body>\r\n<\/html>","created_at":"2016-08-03 19:53:24","updated_at":"2018-07-29 16:51:23"} Details | Department of Computer Science and Engineering, IUB

CEN 306 + Lab: Algorithms

Offered Under: B.Sc. in Computer Engineering (CEN)

Description

Techniques and principles of algorithms design including divide-and-conquer and greedy algorithms. Complexity (worst and average case) analysis and their associated asymptotic notations (Theta, Big O, Omega). Iterative sorting algorithms: Bubble sort, insertion sort. Recursive sorting: merge sort, quick sort, heap sort. Sorting in linear time: counting/radix sort. Decision tree analysis: N*logN bound on comparison based sorting. Algorithms for graph problems: Shortest path (Dijkstra), minimum spanning trees (MST algorithms: Kruskal, Prim). Hashing. Discussion on NP-class problems (e.g. Travelling Salesman Problem).

Prerequisites:

CEN 203 + Lab : Data Structure

Course Type	Major
Credit Hour	4
Lecture Hour	60

Expected Outcome(s):

Students will learn methods for designing efficient algorithms, evaluating their performance, and ways of establishing precise limits on the possible effectiveness of classes of algorithms
They will learn standard algorithms for fundamental problems.

Suggested Books:

Grading Policy:

Biweekly Quiz, Biweekly Programming Assignment, One Midterm Exam, One Final Exam

Letter Grade	Marks	Grade Point
A	90 - 100	4.00
A-	85 - 89	3.70
B+	80 - 84	3.30
B	75 - 79	3.00
B-	70 - 74	2.70
C+	65 - 69	2.30
C	60 - 64	2.00
C-	55 - 59	1.70
D+	50 - 54	1.30
D	45 - 49	1.00
F	00 - 44	0.00