Data Structures and Algorithms Laboratory detailed syllabus for Artificial Intelligence & Machine Learning (AI&ML) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&ML students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Artificial Intelligence & Machine Learning 3rd Sem scheme and its subjects, do visit AI&ML 3rd Sem 2021 regulation scheme. The detailed syllabus of data structures and algorithms laboratory is as follows.
Course Objectives:
- To implement ADTs in Python
- To design and implement linear data structures – lists, stacks, and queues
- To implement sorting, searching and hashing algorithms
- To solve problems using tree and graph structures
List of Experiments:
- Implement simple ADTs as Python classes
- Implement recursive algorithms in Python
- Implement List ADT using Python arrays
- Linked list implementations of List
- Implementation of Stack and Queue ADTs
- Applications of List, Stack and Queue ADTs
- Implementation of sorting and searching algorithms
- Implementation of Hash tables
- Tree representation and traversal algorithms
- Implementation of Binary Search Trees
- Implementation of Heaps
- Graph representation and Traversal algorithms
- Implementation of single source shortest path algorithm
- Implementation of minimum spanning tree algorithms
Course Outcomes:
At the end of the course, the student should be able to:
- Implement ADTs as Python classes
- Design, implement, and analyse linear data structures, such as lists, queues, and stacks, according to the needs of different applications
- Design, implement, and analyse efficient tree structures to meet requirements such as searching, indexing, and sorting
- Model problems as graph problems and implement efficient graph algorithms to solve them
Text Books:
- Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser, Data Structures & Algorithms in Python, John Wiley & Sons Inc., 2013
Reference Books:
- Rance D. Necaise, Data Structures and Algorithms Using Python, John Wiley & Sons, 2011
- Aho, Hopcroft, and Ullman, Data Structures and Algorithms, Pearson Education, 1983.
- Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, Introduction to Algorithms”, Second Edition, McGraw Hill, 2002.
- Mark Allen Weiss, Data Structures and Algorithm Analysis in C++, Fourth Edition, Pearson Education, 2014
For detailed syllabus of all other subjects of Artificial Intelligence & Machine Learning, 2021 regulation curriculum do visit AI&ML 3rd Sem subject syllabuses for 2021 regulation.
For all Artificial Intelligence & Machine Learning results, visit Anna University AI&ML all semester results direct link.