DevelopmentAdded Sep 29, 2026

Data Structures & System Design: Tech Interview Exams

Ace your coding interviews with 200 practice scenarios on Big O, Graph Traversals, Load Balancing, and Microservices.

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Himanshu Kaushik
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Data Structures & System Design: Tech Interview Exams100% OFF
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What you'll learn

Evaluate Time and Space Complexity (Big O Notation) to identify bottlenecks and optimize brute-force code into highly efficient algorithms.
Master core Data Structures and algorithmic paradigms, including Hash Maps, Two Pointers, Dynamic Programming, and Graph Traversals (BFS/DFS).
Architect highly available, distributed backend environments using Load Balancers, API Rate Limiting, and Message Queues (Kafka/RabbitMQ).
Scale databases and memory efficiently utilizing Sharding, Partitioning, and Caching strategies (Redis/Memcached).

Course Description

Writing code that works on your local machine is easy; writing code that works when ten million users log in at the exact same time is engineering. Welcome to the Data Structures, Algorithms & System Design practice assessments! The technical interview process for high-paying engineering roles is notoriously brutal. Interviewers do not just want to see if you can solve the problem—they want to see if you understand the underlying trade-offs between memory, CPU processing, and network latency.

This comprehensive practice test course provides you with 200 expertly crafted, highly unique practice questions designed to simulate the exact difficulty of FAANG-level technical screens. Across these four rigorous practice exams, you will be thrown into high-stakes architectural scenarios. You will test your ability to minimize memory overhead when processing millions of form-filling applications, design highly available backends for nationwide university exam result announcements, and optimize search latency for high-traffic job recruitment portals.

Every single question in this course is unique and includes a detailed explanation of the "why" behind the correct engineering decision. By reviewing these explanations, you will learn industry-standard methodologies for evaluating trade-offs: When should you use a Hash Map instead of an Array? Why is horizontal scaling preferred over vertical scaling in modern cloud architecture? How does a Sliding Window algorithm turn an O(N²) problem into an O(N) solution? If you want to pass the technical screen, negotiate a higher salary, and build systems that scale globally, this is your ultimate testing ground. Enroll today and start optimizing!

Course locale: English (US)

Course instructional level: Advanced Level

Course category: Development

Course subcategory: Software Engineering

Who this course is for:

  • Software Engineers, Backend Developers, and Data Professionals preparing for rigorous technical coding and system design interviews at top-tier technology companies.

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