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Data Structures and Algorithms Syllabus - BCA (TU)

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Course Description

Course Description

Data Structures and Algorithms (CACS201) is a core credit course structured under the official university academic syllabus for Bachelor of Computer Application.

Objective

The objective of this course is to introduce the basic principles, techniques, and applications of Data Structures and Algorithms. Upon the completion students will be able to:

  1. Equip students with deep theoretical foundations in Data Structures and Algorithms.
  2. Develop practical problem-solving, laboratory, and implementation skills.
  3. Prepare graduates for industry careers, research, and national university examinations.

Learning Outcomes

  1. Demonstrate rigorous technical knowledge and conceptual mastery of Data Structures and Algorithms.
  2. Design, implement, and analyze efficient algorithms and practical frameworks.
  3. Solve representative theoretical proofs and complex applied problems independently.

Unit Contents

Course Contents

Unit 1: Introduction to Data Structures and Asymptotic Analysis[6 Hrs.]

Unit 1:Comprehensive study notes, key principles, and examples for Introduction to Data Structures and Asymptotic Analysis.

Unit 2: Linear Data Structures: Stacks and Applications[8 Hrs.]

Unit 2:Comprehensive study notes, key principles, and examples for Linear Data Structures: Stacks and Applications.

Unit 3: Linear Data Structures: Queues and Priority Queues[7 Hrs.]

Unit 3:Comprehensive study notes, key principles, and examples for Linear Data Structures: Queues and Priority Queues.

Unit 4: Linked Lists: Singly, Doubly, and Circular[8 Hrs.]

Unit 4:Comprehensive study notes, key principles, and examples for Linked Lists: Singly, Doubly, and Circular.

Unit 5: Non-linear Data Structures: Trees and Binary Search Trees[9 Hrs.]

Unit 5:Comprehensive study notes, key principles, and examples for Non-linear Data Structures: Trees and Binary Search Trees.

Unit 6: Graphs and Minimum Spanning Trees[9 Hrs.]

Unit 6:Comprehensive study notes, key principles, and examples for Graphs and Minimum Spanning Trees.

Unit 7: Sorting and Searching Algorithms[8 Hrs.]

Unit 7:Comprehensive study notes, key principles, and examples for Sorting and Searching Algorithms.

Teaching Method

Classroom lectures (3 hours/week), practical laboratory assignments (3 hours/week), and project work.

Evaluation Scheme

Internal Assessment (40 Marks: Theory Exam, Practical Exam, Attendance, Assignments) and Final University Board Examination (60 Marks).

Reference Books

  1. Data Structures Using C and C++ by Langsam, Augenstein & Tenenbaum
  2. Introduction to Algorithms by Cormen, Leiserson, Rivest, Stein (CLRS)
Official Syllabus Source:View official university document