2nd Sem, AI&DS

AD3271: Data Structures Design Laboratory syllabus for AI&DS 2021 regulation

Data Structures Design Laboratory detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&DS 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 & Data Science 2nd Sem scheme and its subjects, do visit AI&DS 2nd Sem 2021 regulation scheme. The detailed syllabus of data structures design laboratory is as follows.

Data Structures Design Laboratory

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:

Note: The lab instructor is expected to design problems based on the topics listed. The Examination shall not be restricted to the sample experiments designed.

  1. Implement simple ADTs as Python classes
  2. Implement recursive algorithms in Python
  3. Implement List ADT using Python arrays
  4. Linked list implementations of List
  5. Implementation of Stack and Queue ADTs
  6. Applications of List, Stack and Queue ADTs
  7. Implementation of sorting and searching algorithms
  8. Implementation of Hash tables
  9. Tree representation and traversal algorithms
  10. Implementation of Binary Search Trees
  11. Implementation of Heaps
  12. Graph representation and Traversal algorithms
  13. Implementation of single source shortest path algorithm
  14. 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:

  1. Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser, Data Structures and Algorithms in Python (An Indian Adaptation), Wiley, 2021.
  2. Lee, Kent D., Hubbard, Steve, Data Structures and Algorithms with Python Springer Edition 2015.
  3. Narasimha Karumanchi, Data Structures and Algorithmic Thinking with Python Careermonk, 2015.

Reference Books:

  1. Rance D. Necaise, Data Structures and Algorithms Using Python, John Wiley & Sons, 2011.
  2. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, Introduction to Algorithms”, Third Edition, PHI Learning, 2010.
  3. Mark Allen Weiss, Data Structures and Algorithm Analysis in C++, Fourth Edition, Pearson Education, 2014
  4. Aho, Hopcroft, and Ullman, Data Structures and Algorithms, Pearson Education India, 2002.

For detailed syllabus of all other subjects of Artificial Intelligence & Data Science, 2021 regulation curriculum do visit AI&DS 2nd Sem subject syllabuses for 2021 regulation.

For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.

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