Subject code AD3251 deals with semester II of B.Tech Artificial Intelligence and Data Science regarding affiliated institutions of Anna University Regulation 2021 Syllabus. In this article, you can gather certain information relevant to the data structure design. We added the information by expertise.

We included the proper textbooks and references to assist in some way in your preparation. It will enhance your preparation and strategies to compete with the appropriate spirit with others in the examination. If you see, you can find the detailed syllabus of this subject unit-wise without leaving any topics from the unit. In this article AD3251 – Data Structures Design Syllabus, You can simply read the following syllabus. Hope you prepare well for the examinations. I hope this information is useful. Don’t forget to share with your friends.

If you want to know more about the syllabus of B.Tech Artificial Intelligence And Data Science connected to an affiliated institution’s four-year undergraduate degree program. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.Tech. Artificial Intelligence And Data Science Syllabus Anna University, Regulation 2021.

**Aim of Objectives:**

- To understand the concepts of ADTs.
- To design linear data structures – lists, stacks, and queues.
- To understand sorting, searching, and hashing algorithms.
- To apply Tree and Graph structures.

**AD3251 – Data Structures Design Syllabus**

**Unit I:** Abstract Data Types

Abstract Data Types (ADTs) – ADTs and classes – introduction to OOP – classes in Python – inheritance – namespaces – shallow and deep copying Introduction to analysis of algorithms – asymptotic notations – recursion – analyzing recursive algorithms.

**Unit II:** Linear Structures

List ADT – array-based implementations – linked list implementations – singly linked lists – circularly linked lists – doubly linked lists – applications of lists – Stack ADT – Queue ADT – double-ended queues.

**Unit III:** Sorting And Searching

Bubble sort – selection sort – insertion sort – merge sort – quick sort – linear search – binary search – hashing – hash functions – collision handling – load factors, rehashing, and efficiency.

**Unit IV:** Tree Structures

Tree ADT – Binary Tree ADT – tree traversals – binary search trees – AVL trees – heaps – multi-way search trees.

**Unit V:** Graph Structures

Graph ADT – representations of graph – graph traversals – DAG – topological ordering – shortest paths – minimum spanning trees.

**Text Books:**

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

**References:**

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

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