What will you learn in Data Structures and Performance Course
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Understand how different data structures impact program performance.
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Analyze time and space complexity using Big-O notation.
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Implement efficient data structures such as arrays, linked lists, stacks, queues, trees, and hash tables.
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Optimize algorithms for speed and memory efficiency.
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Compare trade-offs between various data storage approaches.
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Strengthen problem-solving skills for technical interviews and software engineering roles.
Program Overview
Algorithmic Complexity and Performance
⏳ 2–3 weeks
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Learn Big-O, Big-Theta, and Big-Omega notations.
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Analyze time and space complexity of algorithms.
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Understand performance bottlenecks in code.
Linear Data Structures
⏳ 3–4 weeks
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Implement arrays, linked lists, stacks, and queues.
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Compare dynamic vs static memory allocation.
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Evaluate performance trade-offs.
Trees and Hashing
⏳ 3–4 weeks
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Study binary trees and tree traversal techniques.
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Learn hashing fundamentals and collision resolution.
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Optimize data retrieval using hash tables.
Performance Optimization Techniques
⏳ 2–3 weeks
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Improve algorithm efficiency through better structure selection.
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Analyze memory usage patterns.
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Apply optimization strategies in practical coding scenarios.
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Job Outlook
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Essential for aspiring Software Engineers and Backend Developers.
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Highly relevant for technical interview preparation.
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Valuable foundation for advanced algorithms and system design courses.
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Strengthens computational thinking and coding efficiency skills.
