CSCI-2300: Algorithms
Fall 2012        

Announcements.

    Final Exam 12/13/2012 11:30 am -2:30pm - West Hall Auditorium - Covers all the materials

  1. Exam 3 Sample Problems are here and Exam 3 Sample Solutions are here .

  2. Please check your grades in rpilms and see whether all your grades are entered properly . Please resolve with your Lab TA - Please bring the graded papers with you for resolving the conflicts

  3. Lab 10 (11/28/2012) is posted
  4. Home Work 7 is posted
  5. Lab 9 (11/14/2012) is posted
  6. Home Work 6 is posted
  7. If you have lost 5 points in HW 4 on 3.8 for not doing c) part, please get the points back during next Lab (Lab 8)
  8. Sample Test2 is posted
  9. Lab 8 (10/31/2012) is posted
  10. Lab 7 (10/24/2012) is posted
  11. Home Work 5 is posted
  12. Lab 6 (10/17/2012) is posted
  13. Lab 5 (10/10/2012) is posted
  14. Topics of Test 1 is posted
  15. Sample Test 1 (with answers) is posted
  16. Lab 4 (9/26/2012) is posted
  17. Home Work 3 is posted
  18. Lab 3 (9/19/2012) is posted
  19. Lab 2 (9/12/2012) is posted
  20. Home Work 2 is posted
  21. Lab 1 (9/5/2012) is posted
  22. Home Work 1 is posted
  23. Lab 0 (optional 8/29/2012) - Please do not go to the lab is posted
Homework

Exams

Your Grade

 

Course Information

Instructor:         Moorthy

Email:               moorthy@cs.rpi.edu
Office Hours:    Tuesday, Friday 2:00 -3:30pm

Office:              Lally 305

Teaching Asst:Louis Gutierrez (Sec 1 and 7)  
Email:  louisgutierrez2002@gmail.com
Office Hours: Friday 10-12:00 pm
Location:   AE 127?     

Teaching Asst: Haiqiong Li (Sec 5 and 6)
Email: haiqiong.li@gmail.com

Office Hours: W 2-4:00 pm
Location:          AE 125

Teaching Asst: Jon Crall (Sec 2)  
Email: jon.crall@kitware.com       

Office Hours: W 1-2:00 pm  
Location:          AE 127?

Teaching Asst: Shreyas Sekar (Sec 4 and 5)
Email:  shreyas.sekar@gmail.com
Office Hours: T 3-5:00 pm
Location:   Lally 301

Undergraduate Lab TAs:

  1. Lab 1 W 6-7:50 pm Samuel Rhody , Paul Ignatenko
  2. Lab 2 W 2-3:50 pm Manghesh Tamhankar, Bojiang Jin
  3. Lab 4 W Noon-1:50 Bojiang Jin , Dan Ibanez
  4. Lab 5 W 10-11:50 Max Curran, Paul Ignatenko
  5. Lab 6 Noon-1:50 Ben Pringle , Max Curran
  6. Lab 7 W 2-3:50 pm Ben Pringle, Dan Ibanez

Course Objectives

Students at the end of the course will be able to design, implement and analyze algorithms for problems in Science and Engineering. Students will learn different Algorithmic Paradigms and learn techniques for analyzing the algorithms. Students will also learn efficiency both in design and implementation. Students will learn to compare different algorithms for solving the same problem. Students will be exposed to an elementary treatment of NP-complete problems.

Learning Outcome

The goal of this course is to provide a strong foundation in algorithms and data structures in preparation for jobs in industry or for more advanced courses. Algorithms are the basic language of computer science. After taking this course, you, the student, should be able to:
  1. Understand the correctness of, and analyze the running times of, different algorithms.
  2. Use different algorithm-design techniques, including, but not limited to, greedy, divide-and-conquer, and dynamic programming techniques, to solve particular problems.
  3. Model real problems abstractly using the language of graphs and flows.
  4. Solve problems by reducing to other problems whose solution is known, and show that problems are hard by reducing from other problems.
  5. Make intelligent decisions about alternative data structures and algorithmic techniques in the context of practical software problems, choosing from existing data structures and algorithms or designing your own when necessary

Class Time:       Monday and Thursday, 12:00 - 1:20pm
Classroom:       DCC 318
Credits:            4
Prerequisites:    CS2 (CSCI-1200) and Discrete Structures (MATH-2800).

Description

This course discusses algorithms, and the mathematical techniques necessary to design and analyze them.

Web Page: http://www.cs.rpi.edu/~moorthy/Courses/CSCI2300

 

Syllabus

            Chapter 0         Introduction

            Chapter 1         Algorithm with Numbers and Randomized Algorithms

            Chapter 2         Divide and, Conquer Algorithms

            Chapter 3         Decomposition of Graphs

            Chapter 4         Paths in Graphs

            Chapter 5         Greey Algorithms

            Chapter 6         Dynamic Programming

Chapter 8         NP-complete Problems

Chapters 8         Coping with NP-complete Problema

Chapter 7       Linear Programming

 

 

Lectures

            Class 1 (8/27):           Chapter 0                                            

Class 2 (8/30):           Chapter 0 and 1                                            

Class 3 (9/6):           Chapter 1                                                                                

Class 4 (9/10):           Chapter 1                                

Class 5 (9/13):           Chapter 2                                                                               

Class 6 (9/17):            Chapter 2 and 3                                                                     

Class 7 (9/20):            Chapter 3                                                                    

Class 8 (9/24):            Chapter 3 and 4                                            

Class 9 (9/27):          Chapter 4                                                                    

Class 10 (10/1):        Exam 1                                    

Class 11 (10/4):        Chapter 4                                                                    

Class 12 (10/9):         Chapter 5                                                        

Class 13 (10/11):       Chapter 5                                                        

Class 14 (10/15):       Chapter 6                                                        

Class 15 (10/18):       Chapter 6                                                        

Class 16 (10/22):       Chapter 6                                                        

Class 17 (10/25):       Chapter 6 and 8                                            

Class 18 (10/29):       Chapter 8                                                        

Class 19 (11/1):          Chapter 8 and Review                                                                    

Class 20 (11/5):          Exam 2                                    

Class 21 (11/8):        Chapter 8                     .       

Class 22 (11/12):        Chapter 8                     .       

Class 23 (11/15):        Chapter 9                                                                    

Class 23 (11/19):        Chapter 9                                                        

Class 24 (11/26):        Chapter 9                                

Class 25 (11/29):        Chapter 7                                            

Class 26 (12/3):        Chapter 7                                                      

Class 27 (12/5):        Review                                                       

Labs

      6pm - 7:50pm     Sec 1      Eaton 216   Louis/Moorthy (GTA), Samuel Rhody (UTA), Paul Ignatenko (UTA)

      2pm - 3:50pm       Sec 2      Eaton 216Jon (GTA),      Manghesh Tamhankar (UTA)), Bojiang Jin (UTA)    

      Noon - 1:50pm       Sec 4      Sage 2715Shreyas (GTA) Bojiang Jin (UTA), Dan Ibanez (UTA)

      10 am - 11:50am       Sec 5      Sage 2715 Haiqoing/Shreyas (GTA), Max Curran (UTA), Paul Ignatenko (UTA)      

      Noon - 1:50pm       Sec 6      Eaton 216 Haiqoing (GTA), Ben Pringle (UTA), Max Curran (UTA)

      2:00 pm - 3:50pm       Sec 7      Sage 2715 Louis (GTA),Ben Pringle (UTA), Dan Ibanez (UTA)

  1. 8/29 - No Lab - You dont have to go to Lab on August 29th Lab 0 (optional) is posted
  2. Lab 1 (sep 5) Lab 1 is posted(Sep 5)
  3. Lab 2 (Sep 12) Lab 2 is posted (Sep 12)
  4. Lab 3 (Sep 19) Lab 3 is posted (Sep 19)
  5. Lab 4 (Sep 26) Lab 4 is posted (Sep 26)
  6. Lab 5 (Oct 10) is posted (Oct 10)
  7. Lab 6 (Oct 17) is posted (Oct 10)
  8. Lab 7 (Oct 24) is posted
  9. Lab 8 (Oct 31) is posted
  10. Lab 9 (Nov 14) is posted
  11. Lab 10 (Nov 28) is posted

Integrity

Collaboration is not allowed. Homeworks and exams should be solved and written by individuals alone. If anyone is caught cheating then severe measures will be taken such as lowering the final grade, and the event will be reported to the appropriate authorities in the campus.

 

Homework No Late Submissions (unless there is a medical Excuse)

 

Exams (in class exams )

Your Grade

 

Required Text

 

Moorthy
Department of Computer Science
Rensselaer Polytechnic Institute
110 8th Street
Troy, NY 12180