Instructor Profile:
Dr. Purushottam Rohidas Patil
Professor, Computer Science and Engineering, School of Computer Sciences and Engineering, Sandip University, Nashik
Dr. Purushottam Rohidas Patil is a distinguished professor in the Department of Computer Science and Engineering at Sandip University, Nashik, with an extensive teaching experience of 22 years. He has made significant contributions to the field of computer science through both education and research.
Dr. Patil earned his Ph.D. in Computer Science & Engineering from Jodhpur National University, Rajasthan. He holds a Master of Engineering (M.E.) in Computer Science and Engineering from the Government College of Engineering, Aurangabad (Maharashtra), and a Bachelor of Engineering (B.E.) in Computer Engineering from North Maharashtra University, Jalgaon (Maharashtra). His academic background equips him with a solid foundation in both theoretical and practical aspects of computer science.
With a keen research interest in data mining and cybersecurity, Dr. Patil has published 25 research papers in various reputed journals, all indexed in prominent databases such as IEEE and Scopus. His scholarly work not only demonstrates his commitment to advancing knowledge in his field but also reflects his dedication to enhancing the educational experiences of his students through the integration of research and teaching.
Dr. Patil’s expertise and extensive experience make him an invaluable asset to Sandip University and a respected figure in the academic community. His passion for education and research continues to inspire the next generation of computer scientists and engineers.
Course Outline: Design and Analysis of Algorithms
Module 1: Introduction to Algorithms
- Overview of Algorithms: Definition and characteristics of algorithms, Importance of algorithm design and analysis, Applications of algorithms in real-world problems
- Algorithm Representation: Pseudocode and flowcharts, Complexity analysis: Time and Space Complexity, Big O notation, Omega notation, and Theta notation
- Basic Concepts: Problem-solving strategies, Divide and conquer approach, Greedy algorithms and dynamic programming
Module 2: Fundamental Data Structures
- Linear Data Structures: Arrays and linked lists: implementation and applications, Stacks and queues: operations and use cases
- Non-Linear Data Structures: Trees: binary trees, binary search trees, AVL trees, Graphs: representation, types, and traversal algorithms (BFS, DFS)
- Hashing Techniques: Hash tables: design and collision resolution techniques, Applications of hashing in algorithm design
Module 3: Algorithm Design Techniques
- Divide and Conquer Algorithms: Merge sort, quick sort, and their analysis, Binary search and applications
- Dynamic Programming: Principles of dynamic programming, Classic problems: Knapsack problem, longest common subsequence, and matrix chain multiplication
- Greedy Algorithms: Characteristics and strategy, Classic problems: Prim’s and Kruskal’s algorithms, Huffman coding
Module 4: Advanced Topics in Algorithms
- Graph Algorithms: Shortest path algorithms: Dijkstra’s and Bellman-Ford, Minimum spanning tree algorithms
- Complexity Theory: Introduction to NP-completeness and NP-hardness, P vs. NP problem and its significance
- Approximation and Randomized Algorithms: Approximation algorithms for NP-hard problems, Introduction to randomized algorithms and their applications
Course Objectives:
- Develop a strong foundation in algorithm design and analysis.
- Understand various data structures and their impact on algorithm efficiency.
- Apply algorithmic techniques to solve complex computational problems.
- Gain insights into advanced topics in algorithm theory and its real-world applications.
