Courseware in Computer Science

1. Courseware in Computer Science A Presentation For MHRD-NMEICT Project e-PG Pathshala August 18, 2012 AparajitaOjha PDPM Indian Institute of Information Technology, Design & Manufacturing, Jabalpur

2. Available Courseware • MIT Open Courseware (158 graduate courses in Electrical and Computer Engineering) • NPTEL Courses (91 courses in Computer Science and Engineering – for undergraduate, some could be used for graduate programme) • IGNOU • Other Open Universities

3. MIT Open courseware • Video • Lecture notes, • Books, • Tutorials • Assignments and solutions • Projects and examples • Image galleries etc.

4. MIT Open Courseware • OCW scholar • Better support

5. NPTEL Courses • Video • Web

6. Courseware Components Proposal

7. Module Composition • Motivation / Introduction / Continuation of the previous module • Learning Objectives – Module outcome • Content – lectures slides, lecture notes in pdf form. Video to be inserted whenever essential, Links to books whenever available • Supplementary reading links, video lecture links • Useful information – History, state of the art, Important contributors • Summary • Exercises, quizzes, assignments • Implementation Task /Projects

8. Module Features • Multimedia enriched • Animation to be maximally included • Supporting audio • Video • Interactive – quizzes, questions, links and other material

9. A Sample module - Glimpse • Shortest path planning – algorithms

10. What do you see here? • A shortest path from location A to B on a google map !

11. Motivation • Finding a shortest path from a source to a destination is a common real life problem • Examples include -A shortest path on a road network from one location to another for saving time, travel cost or other reasons

12. Motivation • Cell phone seeking signals from the nearest mobile tower on a road network use a shortest path algorithm • Communication network – data flow from a source to another destination in a large computer network requires efficient algorithm for searching shortest routes for fast communication

13. Motivation • Yet, finding a suitable method for determining a shortest path remains a challenge due to the complexities of the networks present in the world • Algorithms exist that facilitate finding shortest paths, called shortest path algorithms

14. Learning Objectives • After going through this module, you should be able to • Understand the purpose of shortest path algorithms • Understand some basic shortest path algorithms • Implement the algorithms on any given network to find a shortest path • And you will be exposed to some of the areas where shortest path algorithms are applied in real world scenario

15. Graphs and Networks • A network can be modeled using a graph G = (V, E) where V is the set of nodes (vertices) and E is the set of edges. • Each edge has some weight attached to it. It can represent traversal time, distance between the two end nodes, cost of traversal or other factors. • Edges can be directed (arcs) or undirected, 849 Mangalore 1843 Bangalore 142 Bhopal Guwahati 802 Hubli 1205 1743 337 1387 2555 1099 Delhi Hyderabad 1233 Nanded 1120

16. Dijkstra’s Algorithm • Edger Dijkstra designed a shortest path algorithm in 1956, which was published in 1959. • Dijkstra’s remark on his algorithm – • One of the reasons that it is so nice was that I designed it without pencil and paper. I learned later that one of the advantages of designing without pencil and paper is that you are almost forced to avoid all avoidable complexities. Eventually that algorithm became, to my great amazement, one of the cornerstones of my fame.

17. Thank You! AparajitaOjha Director and Professor, PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur (India) aojha@iiitdmj.ac.in Phone: 91-761-2632615