Data Structures-Fundamentals

About the Course

This course is designed to start from the basics and help you master Data Structures and Algorithms with coding examples.

Who Should Learn?

This course is perfect for:

Aspiring software engineers preparing for coding interviews.
Students looking to strengthen their problem-solving skills.
Competitive programmers and professionals who want to refine their DSA knowledge.

Why Learn With Us?

Expert Instructor: The course is taught by a Data Structures expert and author of a well-known DSA book.
Hands-on Learning: Every hour has theory and hands-on bundled in it.
Structured Curriculum: A well-defined path covering fundamental and advanced concepts.

Meet the Instructor

Dr. S. Lovelyn Rose

Meet Dr.S.Lovelyn Rose, a Doctorate in AI, who has had years of academic and research experience at PSG College of Technology. She has worked extensively in both research and productionizing code as the CTO and Head of AI Research at Brainmage AI Inc. In addition, she serves as an AI consultant for startups and enterprises, helping businesses integrate AI-driven solutions into their operations. Passionate about education, she has authored books on "Data Structures" and "Deep Learning", making complex AI concepts accessible to learners worldwide.

Course Content

Arrays

Start with the simplest and most efficient data structures

1D Array - Definition, properties, and memory representation
Array Indexing - Traversal, slice and dice in arrays
Operations - Insertion, deletion, traversal
2D Arrays - Definition, representation, matrix manipulation

Searching

Perform search operation on arrays

Linear Search - Code, best, worst, and average case complexity
Binary Search - Code, O(log n) analysis

Sorting

Learn the common O(n2) and O(n log n) complexity sorting techniques.

Insertion Sort - Code, best and worst case complexity
Selection Sort - Code, best and worst case complexity
Bubble Sort - Code, best and worst case complexity
MergeSort - Recurrence trees, Python code, time and space complexity
QuickSort - Recurrence trees, Python code, time and space complexity

Linked Lists

Manipulate all types of linked lists

Singly Linked Lists - Definition, operations (insertion, deletion, searching)
Doubly Linked Lists - Definition, operations (insertion, deletion, searching)
Circular Linked Lists - Definition, operations (insertion, deletion, searching)

Stacks and Queues

Understand the working of stacks and queues and solve applications using them.

Stacks - Operations, infix to postfix conversion, evaluation
Queues - Circular queues, Deque operations

Trees

Manipulate trees using arrays and linked lists

Tree Types - Binary trees, representation
Traversal - Inorder, preorder, postorder
Binary Search Trees - Definition, insertion, deletion, searching
AVL Trees - Definition, insertion, deletion, searching
Tries - Definition, insertion, deletion, searching
Heaps and Priority Queues - Insertion, deletion, sorting

Graphs

Manipulate graphs using arrays and linked lists

Terminologies - Types of graphs
Representation - Arrays, linked lists
Traversal - Depth-first, breadth-first
Shortest Path Algorithms - Dijkstra, Floyd

Course Fee and Duration

Course Fee: ₹7999/-

Duration: 30 hours of instructor-led training.

FAQs

Do I need prior experience? - Basic programming knowledge is recommended.
Will I get a certificate? - Yes, a certificate will be provided upon completion.