Useful data structure study and algorithms implemented with python, practing for technical interviews, live coding and leet problems Also, leet code preparation road map, around 8-12 weeks long.
- Two-pointer technique
- Sliding window
- Fast and slow pointers
- Tree traversal
- Depth-first search (DFS)
- Binary search
- Dynamic programming
Goal: Familiarize yourself with common data structures and algorithms, and solve easy-level questions to build confidence.
1- Review Core Concepts:
- Arrays & Strings: Basics of iteration, manipulation, and string operations.
- Hash Maps & Sets: Learn how to solve problems using these for faster lookups.
- Sorting: Learn basic sorting algorithms and when to use them.
- Time Complexity: Understand Big O notation and analyze solutions.
2- Practice Topics:
- Arrays & Strings: Easy questions (e.g., Two Sum, Best Time to Buy and Sell Stock)
- Hash Maps: Practice frequent problems (e.g., Contains Duplicate, Valid Anagram)
- Sorting: Learn and apply basic algorithms like quicksort or mergesort.
- Goal: Solve at least 10-15 easy questions per topic.
Goal: Move to intermediate-level questions focusing on the most common algorithms asked in interviews.
1- Core Topics to Focus On:
- Binary Search: Learn how to apply it in sorted data (e.g., Search Insert Position).
- Linked Lists: Practice operations on singly and doubly linked lists (e.g., Reverse Linked List).
- Stacks & Queues: Use these data structures for questions involving sequence (e.g., Valid Parentheses, Min Stack).
- Binary Trees & BST: Familiarize yourself with traversals, depth-first and breadth-first searches.
- Recursion & Backtracking: Solve problems like permutations and combinations (e.g., Subsets, Combination Sum).
2- Practice Strategy:
- Start by learning the theory, then solve 5-10 questions on each topic.
- Review solutions and understand different approaches (e.g., iterative vs. recursive).
Goal: Focus on harder and more complex problem-solving skills, including optimization.
1- Key Advanced Topics:
- Dynamic Programming: Solve questions that involve memoization (e.g., Climbing Stairs, Coin Change).
- Graphs: Practice BFS/DFS and shortest path algorithms (e.g., Course Schedule, Number of Islands).
- Heap & Priority Queues: Understand heap operations and use them in questions (e.g., Kth Largest Element).
- Advanced Trees & Tries: Practice problems involving more complex tree structures.
- Greedy Algorithms: Solve questions where locally optimal choices lead to the global optimum (e.g., Jump Game, Gas Station).
2- Practice Strategy:
- Spend extra time reviewing dynamic programming problems, as these are common in interviews.
- Solve at least 5-10 questions per advanced topic.
Goal: Simulate interview conditions by solving problems in a timed environment.
1- Simulate Interviews:
- Pick random medium and hard problems and try to solve them within 30-45 minutes.
- Focus on verbalizing your thought process, as you would in an actual interview.
- Use mock interview platforms or ask a friend to conduct mock interviews with you.
2- Topic Revision:
- Target Weak Areas: Revisit the questions or topics where you struggled the most.
- Mixed Practice: Do random LeetCode questions to simulate real interview randomness.
- LeetCode Contests: Participate in LeetCode Weekly Contests for more variety and pressure handling.
Goal: Strengthen your confidence and optimize speed before the interview.
1- Daily Problem Solving:
- Solve a mixture of easy, medium, and hard problems.
- Focus on efficiency and correctness.
- Do some pair programming to get used to coding with someone watching.
2- System Design & Behavioral Practice:
- If applying for senior roles, start reviewing system design concepts.
- Also, practice answering behavioral questions and explaining the thought process for algorithmic problems.
DSA and leer code peoblems