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Data Structures & Algorithms (Python): Practice Exams
New
100 students

Data Structures & Algorithms (Python): Practice Exams

Ace technical coding interviews with 200 questions on Big O, Graphs, Hash Maps, and Dynamic Programming.
New
Created byHimanshu Kaushik
Last updated 6/2026
English

What you'll learn

  • Evaluate algorithmic efficiency by calculating Big O Time and Space Complexity for worst-case, average-case, and best-case scenarios.
  • Select the optimal underlying data structures—including Hash Maps, Linked Lists, Stacks, and Queues—to solve complex engineering bottlenecks.
  • Traverse hierarchical and relational data efficiently using Trees (BST, AVL) and Graph traversal algorithms (BFS, DFS).
  • Optimize brute-force recursion by implementing Dynamic Programming techniques (Memoization and Tabulation) and efficient Sorting Algorithms.

Included in This Course

200 questions

  • Data Structures & Algorithms (Python): Practice Exams Set-150 questions
  • Data Structures & Algorithms (Python): Practice Exams Set-250 questions
  • Data Structures & Algorithms (Python): Practice Exams Set-350 questions
  • Data Structures & Algorithms (Python): Practice Exams Set-450 questions

Description

Writing code that works is easy; writing code that scales to millions of users without crashing the server is what separates junior developers from senior engineers. Welcome to the Python Data Structures & Algorithms (DSA) practice assessments! If you are applying for a software engineering role at any major tech company, you will face a technical coding interview. Interviewers do not just want to see if you can solve the problem—they want to see if you can solve it efficiently.

This comprehensive practice test course provides you with 200 realistic, highly technical questions modeled directly after the core conceptual questions asked in FAANG (Facebook, Amazon, Apple, Netflix, Google) technical screens. Across these four rigorous practice exams, you will face scenario-based engineering challenges. You will determine the most mathematically efficient way to implement undo/redo states for graphic design tools (Stacks), find the shortest path in logistics routing apps (BFS/Graphs), and optimize high-frequency trading matching engines.

The questions in this course cut through the fluff and dive straight into computer science fundamentals. You will be challenged on the exact Big O complexity of Merge Sort, the structural rules of a Binary Search Tree, and the memory trade-offs of using Hash Maps. If you are preparing to tackle LeetCode problems, gearing up for an intense whiteboard interview, or simply wanting to write faster, cleaner Python code, this is your ultimate testing ground. Enroll today and start optimizing!

Course locale: English (US)

Course instructional level: Intermediate Level

Course category: Development

Course subcategory: Software Engineering

Who this course is for:

  • Aspiring Software Engineers, Backend Developers, and Data Scientists preparing for grueling technical coding interviews (LeetCode/HackerRank style) at top-tier technology companies.

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