Παρουσίαση/Προβολή
(TP324) - A. MALAMOS
Περιγραφή Μαθήματος
|
A. COURSE OUTLINE |
|
|
1. Course Title / Type Open Algorithms ü Mandatory ❏ Selective |
4. Subject Area ❏ Information Systems ❏ Networks ❏ Computer Science ❏ Multimedia ❏ Intelligent Systems |
|
2. School / Program STEF / Postgraduate ‘Informatics & Multimedia’ |
|
|
3. Author contact details 1) Name: A.G. Malamos 2) Title/Position: Assoc. Professor 3) Phone: 2810 379884 4) E-mail: amalamos@epp.teicrete.gr |
|
|
Brief Course Description
The course commands a central role in computer science it both theoretical and practical levels, in many cases covering themes beyond the subject of informatics. The course strives for students to understand fundamental ways or data organization in computer memory and to learn and implement techniques for the handling of that data. Special attention is placed on creating new data algorithms with an obvious result on the dexterities of students to handle such problems. |
|
B. COURSE CONTENT
Week 1 & 2:
|
Detailed description |
Review on Data Structures and Applications |
|
Expected outcomes |
Student would be able to: 1.Understand terminology and infrastructure on data Structures 2. Work with Data Structures and the corresponding computational techniques |
|
Tutorial exercise |
Assignments |
|
Learning materials |
Th.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, “Introduction to Algorithms” 3rd edition, MIT Press |
Week 3 & 4:
|
Detailed description |
Graphs Search in graphs, Paths in graphs, Distances, Lengths on edges, Dijkstra's algorithm, Priority queue implementations, Shortest path.
|
|
Expected outcomes |
Student would be able to: 1.Understand issues on arithmetic calculations and fundamental terms in Graphs 2. Work with Graphs |
|
Tutorial exercise |
Assignments |
|
Learning materials |
Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, MC Graw Hill Higher Education Edition |
Week 5 & 6:
|
Detailed description |
Greedy algorithms Minimum spanning trees, Huffman encoding |
|
Expected outcomes |
Student would be able to identify and design greedy algorithms |
|
Tutorial exercise |
Assignments |
|
Learning materials |
Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, MC Graw Hill Higher Education Edition |
Week 7 & 8:
|
Detailed description |
Dynamic programming Shortest paths, Longest increasing subsequences, Knapsack |
|
Expected outcomes |
Student would be able to identify and design dynamic programming algorithms |
|
Tutorial exercise |
Assignments |
|
Learning materials |
Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, MC Graw Hill Higher Education Edition |
Week 9 & 10:
|
Detailed description |
Simplex algorithms and Linear Programming Linear Programming, feasible solutions, geometry of linear programming, Duality, max-flow, min-cut, labeling algorithm, Dijkstra algorithm |
|
Expected outcomes |
Student would be able to work with fundamental theoretical issues in linear programming and geometry of solutions |
|
Tutorial exercise |
Assignments |
|
Learning materials |
C. H. Papadimitriou, Keneth Steinglitz“ Combinatorial Optimization”, Dover Publications |
Week 11:
|
Detailed description |
Algorithms and Complexity Computability, Time bounds, polynomial time algorithms, |
|
Expected outcomes |
Student would be able to estimate computational criteria in algorithms |
|
Tutorial exercise |
|
|
Learning materials |
C. H. Papadimitriou, Keneth Steinglitz“ Combinatorial Optimization”, Dover Publications |
Week 12 & 13:
|
Detailed description |
NP-Problems Discussion about NP problems, Backtracking, Branch and Bound |
|
Expected outcomes |
Students would be able to work and understand NP complexity problems |
|
Tutorial exercise |
Assignments |
|
Learning materials |
Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, MC Graw Hill Higher Education Edition C. H. Papadimitriou, Keneth Steinglitz“ Combinatorial Optimization”, Dover Publications |
Week 14:
|
Detailed description |
Review of the subject Discussion about NP problems, Backtracking, Branch and Bound |
|
Expected outcomes |
Student would be able to work and understand NP complexity problems |
|
Tutorial exercise |
Assignments |
|
Learning materials |
|
T Cormen, C Leiserson, R Rivest and C Stein, "Introduction to Algorithms", MIT Press; 3rd edition
Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, MC Graw Hill Higher Education Edition
C. H. Papadimitriou, Keneth Steinglitz, “Combinatorial Optimization”, Dover Publications
Ημερομηνία δημιουργίας
Τρίτη 24 Φεβρουαρίου 2015
-
Δεν υπάρχει περίγραμμα