Course Includes:
- Price: FREE
- Enrolled: 0 students
- Language: English
- Certificate: Yes
- Difficulty: Advanced
Coupon verified 12:30 PM (updated every 10 min)
Course Folder
What You'll Learn
- Master core data structures — arrays
- linked lists
- stacks
- queues
- trees
- tries
- and graphs — through 600 practice questions,Solve algorithmic problems using two pointers
- sliding windows
- binary search
- and recursion/backtracking techniques,Build fluency in dynamic programming
- greedy algorithms
- and proving algorithm correctness with exchange arguments,Analyze time and space complexity
- recognize NP-hard problems
- and prepare for technical coding interviews
Requirements
- Basic programming knowledge in any language is recommended (examples use Python-style pseudocode). No prior data structures or algorithms coursework is required — each test builds from fundamentals through advanced techniques
- making this suitable for beginners as well as developers preparing for technical interviews.
Description
Master Data Structures & Algorithms through 600 carefully crafted practice questions spanning everything from array fundamentals to advanced graph theory and complexity analysis.
This course is organized into six comprehensive practice tests, each with 100 multiple-choice questions. Every question includes a detailed explanation for all four answer options, not just the correct one, so you understand the reasoning behind each concept rather than simply memorizing answers.
Test 1: Arrays, Strings & Two Pointers/Sliding Window — Two-pointer techniques, sliding windows, binary search, hash maps, and classic algorithms like Kadane's and the Dutch National Flag problem.
Test 2: Linked Lists, Stacks & Queues — Fast-and-slow pointers, cycle detection, the LRU cache, monotonic stacks, and stack/queue implementation tradeoffs.
Test 3: Trees, Tries & Graphs — Binary search trees, tree traversal, tries, BFS/DFS, topological sort, union-find, and shortest-path algorithms.
Test 4: Sorting, Searching, Recursion & Backtracking — Merge sort, quicksort, heap sort, N-Queens, Sudoku-solving, and advanced binary search variants.
Test 5: Dynamic Programming — Knapsack, longest common subsequence, interval DP, state-machine DP, and recognizing when greedy shortcuts genuinely apply.
Test 6: Advanced Graphs, Greedy Algorithms & Complexity Analysis — Bellman-Ford, Floyd-Warshall, exchange-argument proofs, NP-completeness, and approximation algorithms.
Whether you're preparing for technical interviews, filling gaps from self-taught learning, or sharpening algorithmic intuition as a working engineer, this course gives you a structured, thorough way to test and deepen your understanding.
Who this course is for:
- This course is for anyone preparing for technical coding interviews at software companies
- computer science students wanting structured practice beyond their coursework
- and self-taught developers looking to build a genuine
- interview-ready understanding of data structures and algorithms. Its also well-suited for engineers who already write code professionally but want to sharpen their algorithmic problem-solving — recognizing when to use a hash map versus a two-pointer approach
- when greedy reasoning is provably correct versus when dynamic programming is genuinely required
- and how to analyze the time and space complexity of their own solutions.
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