Data Structures and Algorithms Complete Course (freeCodeCamp)

Overview

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

Objectives

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

Unit structure

• Unit 1: Introduction to Data Structures and Asymptotic Analysis6 hrs

  By the end of Unit 1, students will be able to explain, implement, and solve problems related to Introduction to Data Structures and Asymptotic Analysis.

  Unit 1:Comprehensive study notes, key principles, and examples for Introduction to Data Structures and Asymptotic Analysis.
• Unit 2: Linear Data Structures: Stacks and Applications8 hrs

  By the end of Unit 2, students will be able to explain, implement, and solve problems related to Linear Data Structures: Stacks and Applications.

  Unit 2:Comprehensive study notes, key principles, and examples for Linear Data Structures: Stacks and Applications.
• Unit 3: Linear Data Structures: Queues and Priority Queues7 hrs

  By the end of Unit 3, students will be able to explain, implement, and solve problems related to Linear Data Structures: Queues and Priority Queues.

  Unit 3:Comprehensive study notes, key principles, and examples for Linear Data Structures: Queues and Priority Queues.
• Unit 4: Linked Lists: Singly, Doubly, and Circular8 hrs

  By the end of Unit 4, students will be able to explain, implement, and solve problems related to Linked Lists: Singly, Doubly, and Circular.

  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 Trees9 hrs

  By the end of Unit 5, students will be able to explain, implement, and solve problems related to Non-linear Data Structures: Trees and Binary Search Trees.

  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 Trees9 hrs

  By the end of Unit 6, students will be able to explain, implement, and solve problems related to Graphs and Minimum Spanning Trees.

  Unit 6:Comprehensive study notes, key principles, and examples for Graphs and Minimum Spanning Trees.
• Unit 7: Sorting and Searching Algorithms8 hrs

  By the end of Unit 7, students will be able to explain, implement, and solve problems related to Sorting and Searching Algorithms.

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

Learning outcomes

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

Teaching & evaluation

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

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

Reference books

• Data Structures Using C and C++ by Langsam, Augenstein & Tenenbaum
• Introduction to Algorithms by Cormen, Leiserson, Rivest, Stein (CLRS)