DSA Competitive Programming - Practice Questions 2026
Course Overview
What You'll Learn
- Retakeability: You can retake the exams as many times as you want to ensure total mastery.
- Original Question Bank: This is a huge, original question bank curated by industry experts.
- Expert Support: You get direct support from instructors if you have questions regarding specific logic or edge cases.
- Detailed Explanations: Every single question includes a comprehensive breakdown of the logic used.
- On-the-go Learning: Fully mobile-compatible via the Udemy app.
- Risk-Free: We offer a 30-day money-back guarantee if you are not satisfied with the content.
About This Free Course
Master DSA Competitive Programming: Ultimate Practice Exams
Welcome to the definitive practice resource designed to help you master Data Structures and Algorithms (DSA) for Competitive Programming. Whether you are preparing for top-tier coding contests or technical interviews at FAANG companies, these practice exams provide the rigorous environment you need to sharpen your problem-solving skills and improve your time complexity analysis.
Why Serious Learners Choose These Practice Exams
Competitive programming is not just about knowing the syntax; it is about recognizing patterns and applying the most efficient algorithm under pressure. Serious learners choose this course because it mimics the environment of platforms like Codeforces, LeetCode, and CodeChef.
Retakeability: You can retake the exams as many times as you want to ensure total mastery.
Original Question Bank: This is a huge, original question bank curated by industry experts.
Expert Support: You get direct support from instructors if you have questions regarding specific logic or edge cases.
cissp exam tests 500 questions detailed explanations 2026: Every single question includes a comprehensive breakdown of the logic used.
On-the-go Learning: Fully mobile-compatible via the Udemy app.
Risk-Free: We offer a 30-day money-back guarantee if you are not satisfied with the content.
Course Structure
This course is meticulously organized to take you from foundational logic to high-level algorithmic mastery.
Basics / Foundations: Focuses on the building blocks of programming including Time and Space Complexity (Big O notation), recursion fundamentals, and basic array manipulations.
Core Concepts: Covers essential data structures like Linked Lists, Stacks, Queues, and Binary Trees. You will learn how to implement and traverse these structures efficiently.
Intermediate Concepts: Dives into sorting and searching algorithms, Heaps (Priority Queues), and Hashing techniques. This section bridges the gap between simple data storage and optimized retrieval.
Advanced Concepts: Explores complex topics such as Dynamic Programming (DP), Graph Theory (Dijkstra’s, MST, Flow), Segment Trees, and Fenwick Trees.
Real-world Scenarios: Challenges you with problems that simulate actual software engineering hurdles, requiring you to combine multiple data structures for an optimal solution.
Mixed Revision / Final Test: A comprehensive evaluation featuring a random mix of all topics to test your ability to identify the correct approach without topical hints.
Sample Practice Questions
QUESTION 1
What is the time complexity of building a binary heap from an unsorted array of $n$ elements?
$O(1)$
$O(\log n)$
$O(n)$
$O(n \log n)$
$O(n^2)$
CORRECT ANSWER: 3
CORRECT ANSWER EXPLANATION: While inserting $n$ elements one by one takes $O(n \log n)$, the "Build-Heap" algorithm (bottom-up heapify) runs in $O(n)$ because the work decreases as you move up the tree.
WRONG ANSWERS EXPLANATION:
Option 1: Building a heap requires processing all elements, so it cannot be constant time.
Option 2: This is the complexity of a single insertion or deletion, not the whole build process.
Option 4: This is the complexity if you use the naive method of $n$ successive insertions.
Option 5: This is inefficient and would only occur in poorly implemented sorting algorithms like bubble sort.
QUESTION 2
Which of the following data structures is most efficient for checking if a cycle exists in an undirected graph?
Stack
Queue
Disjoint Set Union (DSU)
Linked List
Min-Heap
CORRECT ANSWER: 3
CORRECT ANSWER EXPLANATION: DSU with path compression and union by rank provides near-constant time operations to detect cycles by checking if two vertices already belong to the same set.
WRONG ANSWERS EXPLANATION:
Option 1: While a Stack can be used in DFS for cycle detection, it is not a "data structure for checking" but rather a tool for traversal.
Option 2: Queues are used in BFS; while BFS can detect cycles, DSU is generally more specialized and efficient for this specific property.
Option 4: A Linked List has no inherent properties to manage graph connectivity or cycles efficiently.
Option 5: Heaps are used for ordering elements by priority, not for tracking connectivity.
QUESTION 3
In Dynamic Programming, what is the main difference between "Tabulation" and "Memoization"?
Tabulation is Top-Down; Memoization is Bottom-Up.
Tabulation uses recursion; Memoization uses loops.
Tabulation is Bottom-Up; Memoization is Top-Down.
Tabulation uses more memory than Memoization.
There is no difference; they are synonyms.
CORRECT ANSWER: 3
CORRECT ANSWER EXPLANATION: Tabulation starts from the base cases and builds up to the solution using iterations (Bottom-Up). Memoization starts from the main problem and caches results of subproblems using recursion (Top-Down).
WRONG ANSWERS EXPLANATION:
Option 1: This is the exact opposite of the correct definitions.
Option 2: Generally, Tabulation uses loops and Memoization uses recursion.
Option 4: Both typically use $O(n)$ space for storage, though Tabulation can sometimes be optimized further.
Option 5: They are different strategies for implementing DP solutions.
We hope that by now you're convinced! There are hundreds of additional questions inside the course designed to push your limits.
Who Should Take This Course
"DSA Competitive Programming - Practice Questions 2026" is aimed at people who want a practical, structured introduction to development without paying full price for it. It's a solid fit if you're starting out in development and want a guided course rather than piecing tutorials together yourself, if you've tried free YouTube content on the topic and want something more organized, or if you already work in a related area and want a refresher you can finish at your own pace. Since enrollment happens on Udemy itself, you keep full access to view the lectures, download any provided resources, and revisit the material later — this isn't a stripped-down or time-limited version of the course.
Why This Course Is Worth Taking
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Pros & Cons
👍 Pros
- 100% free to enroll via this coupon (normally $34.99)
- Lifetime access on Udemy once enrolled, even after the coupon expires
- Rated 4.5/5 by past students on Udemy
- Self-paced — no fixed schedule or live sessions to attend
👎 Cons
- Coupon is time-limited and can expire before you enroll
- No live instructor support — questions go through Udemy's Q&A, not us
- Certificate is a Udemy completion certificate, not an accredited qualification
Frequently Asked Questions
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