Scientific Computing Pune University

Hi buddy I want to do M. Sc. (Scientific Computing) course from pune university and for the same here I am looking for its syllabus , can you plz provide me here ??

[Rajkumar Agarwal]

As you asking for pune university. Sc. (Scientific Computing) course syllabus , so on your demand I am providing same for you :

SC – 101 Principles of Programming Languages
1. Introduction and Motivation
[8 hrs]
Idea of analyzing an algorithm through examples, introduction to some notations,
comparison of algorithms, notions of space and time efficiency and motivation for
algorithm design methods, demonstration of algorithm analysis for some suitable
example algorithm, say merge sort.
2. Algorithm Analysis Techniques
[12 hrs]
(a) Asymptotic Analysis
Detailed coverage of asymptotic notations and analysis. Big Omicron, Big Theta,
Big Omega, Small theta, Small omega. Comparison of the Insertion Sort and the
Merge Sort Algorithms.
(b) Recurrence Analysis
Introduction to Recurrence equations and their solution techniques (Substitution
Method, Recursion Tree Method, and the Master Method), Proof of the Master
Method for solving Recurrences. Demonstration of the applicability of Master
Theorem to a few algorithms and their analysis using Recurrence Equations.
(Example algorithms: Binary Search, Powering a number, Strassen's Matrix
Multiplication)
(c) Analysis of more Sorting algorithms: Quick Sort and Counting Sort
3. Algorithm Design Techniques
[12 hrs]
(a) Types of Algorithms
(b) Dynamic Programming
Introduction and the method for constructing a DP solution, illustrative problems,
e.g. assembly line scheduling problem using DP, or solution for the matrix chain
multiplication.
(c) Greedy Algorithms
Greedy vs. DP, methodology, illustrative problems, e.g. the knapsack problem
using a greedy technique, or activity selection Problem. Construction of Huffman
Codes.
(d) Backtracking
Introduction to recursion, solving the 0-1 Knapsack problem using backtracking,
pruning in backtracking and how it speeds up the solution for the 0-1 Knapsack
problem.
(e) Branch and Bound
Description and comparison with backtracking, the FIFO B&B and the Max Profit
B&B using the 0-1 Knapsack problem
4. Graph Theory
[12 hrs]
(a) Breadth First and Depth First Search Algorithms
(b) Minimum Spanning Trees, Kruskal's Algorithm
(c) Minimum Spanning Trees, Prim's Algorithm
(d) Properties of Shortest paths.
(e) Dijkstra's Algorithm
(f) Bellman Ford Algorithm
5. NP-Completeness
[12 hrs]
(a) Polynomial time
(b) Polynomial time verification (NP problems)
(c) Concept of NP-Hard with example (Halting problem)
(d) NP-Completeness and Reducibility (without proof)
(e) Some NP-Complete problems
(f) Overview of showing problems to be NP-Complete

Pune University. Sc. (Scientific Computing) course syllabus