Data Structures and Algorithms (AT70.02) Comp. Sc. and Inf. Mgmt. Asian Institute of Technology.

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Data Structures and Algorithms (AT70.02) Comp. Sc. and Inf. Mgmt. Asian Institute of Technology

Course Overview Page 1 Instructor: Prof. Sumanta Guha Office: 104 CSIM Building Telephone: 5714 Prerequisite: Officially none, but we’ll assume you have had an undergrad DSA course and have decent programming skills. Course Website: All lecture slides – and these slides – are on-line !

Course Overview Page 2 Class times: Mon. & Th. 16:00-17:30 Discussion Group: Yahoo group – ait_csim_dsa WWW: You must join the group! Membership is currently open so anyone can join – just go to the link above and click the join button. If you have a problem send me mail and I will invite you. Important: It’s good for everyone to post questions and comments to the discussion group!! Then, everybody benefits from the interaction. Announcements by the instructor will always be posted to the group. However, if you wish to see me in my office you are always welcome (provided I am not busy). It’s best to make an appointment. Note that I am not a morning person. Please check the group frequently and please participate in discussions

Course Overview Page 3 Required Textbook: Cormen, Leiserson, Rivest, Stein – Introduction to Algorithms (2 nd Edition), McGraw Hill, 2001 Reference Books : Goodrich, Tamassia – Data Structures and Algorithms in Java (4 th Edition), John Wiley & Sons, 2005 Weiss – Data Structures and Problem Solving Using C++ (2 nd Edition), Addison Wesley, 2000 Sedgewick – Algorithms in C++ (3 rd Edition), Addison Wesley, 1998

Course Overview Page 4 Tentative Course Outline (from course textbook CLRS “Introduction To Algorithms”): Chap. 2: Getting Started Chap. 3: Growth of Functions Chap. 4: Recurrences Chap. 5: Prob. Analysis and Randomized Algorithms Chap. 6: Heapsort Chap. 7: Quicksort Chap. 8: Sorting in Linear Time Chap. 9: Medians and Order Statistics Chap. 11: Hash Tables Chap. 13: Red-Black Trees Chap. 15: Dynamic Programming Chap. 16: Greedy Algorithms Chap. 18: B-Trees Chap. 24: Single-Source Shortest Paths Chap. 26: Maximum Flows Chap. 30: Polynomials and the FFT Chap. 32: String Matching Chap. 33: Computational Geometry Undergrad material: will be covered quickly!

Course Overview Page 5 Grading System: Mid-sem – 40% Final – 60% Enjoy the Course! Be enthusiastic about the material because it is interesting, useful and an important part of your training as a computer scientist. Our job is to help you learn and enjoy the experience. We will do our best but we need your help. So let’s all have fun together with data structures and algorithms!!!