What will you learn in Data Structures Course
Understand core data structures: arrays, linked lists, stacks, queues, trees, and graphs.
Learn dynamic arrays and amortized analysis for efficient memory and performance management.
Explore priority queues, disjoint sets, and hash tables with O(1) average-time operations.
Implement data structures in multiple languages (C++, Java, Python) through programming assignments.
Apply data structures to solve real-world problems, like file storage optimization and scheduling.
Gain insights into trade-offs and performance analysis of different data structures.
Program Overview
Module 1: Basic Data Structures
⏳ 4 hours
Study arrays, singly/doubly linked lists, stacks, queues, trees, and tree traversals.
Includes 7 videos, 7 readings, 1 assignment, and 1 programming assignment.
Module 2: Dynamic Arrays and Amortized Analysis
⏳ 48 minutes
Learn dynamic arrays and methods for amortized cost analysis: aggregate, banker’s, and physicist’s methods.
Includes 5 videos, 1 reading, and 1 assignment.
Module 3: Priority Queues and Disjoint Sets
⏳ 5 hours
Explore priority queues, heap implementations, and disjoint set data structures.
Understand applications in scheduling, shortest-path algorithms, and big data processing.
Modules 4–6
⏳ Various hours
Advanced topics including balanced trees, hash tables, graph representations, and algorithmic applications.
Programming assignments reinforce implementation and problem-solving skills.
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Job Outlook
Prepares learners for software development, algorithm design, and competitive programming.
Skills are crucial for roles such as Software Engineer, Data Engineer, and Backend Developer.
Enhances understanding of efficient data storage, retrieval, and algorithm optimization.
Provides foundational knowledge for advanced courses in algorithms, databases, and big data.
Specification: Data Structures
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