Summary of "90 Days of MAANG Roadmap | Data strcutre + System Design"
Summary of “90 Days of MAANG Roadmap | Data structure + System Design”
This video presents a detailed 90-day structured roadmap designed to prepare candidates for interviews at MAANG-level companies (Meta, Apple, Amazon, Netflix, Google). The strategy is divided into three phases of 30 days each, focusing on foundational data structures, advanced data structures, and system design plus mock interviews, respectively. The roadmap emphasizes consistent practice, understanding concepts deeply rather than rote learning, and balancing data structures with system design preparation.
Main Ideas and Concepts
- Goal: Transform from solving random DSA problems to becoming an interview-ready candidate for MAANG companies in 90 days.
- Structure: 90 days divided into three 30-day phases:
- Phase 1: Foundation of data structures and programming language basics.
- Phase 2: Advanced data structures and recursion.
- Phase 3: System design and mock interviews, including behavioral questions.
- Approach: Focus on understanding concepts, implementing data structures from scratch, practicing selected problems by difficulty, and revising regularly.
- Balance: Equal focus on data structures and system design, with behavioral questions also included.
Detailed 90-Day Roadmap Breakdown
Phase 1: Foundation of Data Structures (Days 1-30)
Week 1: Mastering a Programming Language
- Choose one language (C++, Java, Python).
- Focus on syntax basics: input/output, conditions, loops, functions, arrays, lists, hashmaps.
- Practice simple problems like factorial, digit counting, checking sorted arrays.
- Write clean, understandable code; understand program flow instead of copy-pasting.
Week 2: Arrays and Strings
- Arrays and strings cover ~40% of interview questions.
- Focus on key patterns: sliding window, two pointers, prefix sum, string manipulation.
- Practice problems: Two Sum, longest substring without repeating characters, valid palindrome.
- Understand when and why to use each pattern.
Week 3: Linked Lists
- Understand singly, doubly, and circular linked lists.
- Implement all types from scratch to grasp node connections and references.
- Focus on singly linked list problems: reverse linked list, detect cycles, merge sorted lists.
- Use pen and paper to visualize node operations before coding.
Week 4: Stacks and Queues
- Implement stacks and queues from scratch using arrays and linked lists.
- Practice problems: next greater element, previous smaller element, minimum stack, valid parentheses, postfix/prefix evaluation.
- Understand why to use stack vs. queue for each problem.
General Tip for Phase 1
- Solve 30 problems per topic: 10 easy, 15 medium, 5 hard.
- Do not move to the next topic until these are solved.
Phase 2: Advanced Data Structures (Days 31-60)
Week 5: Recursion and Backtracking
- Critical for trees, graphs, and dynamic programming.
- Practice problems: Rat in a Maze, N-Queens, subsets and permutations of arrays.
- Understand function calls, stack activation records, and recursion flow.
Week 6: Binary Search and Its Patterns
- Two main types: binary search on sorted arrays and binary search on answers.
- Practice easy problems first: search insert position, rotated sorted array, first/last occurrence.
- Advanced problems: aggressive cows, eating bananas, book allocation.
- Understand why and when binary search reduces complexity.
Week 7: Trees and Graphs
- Trees:
- Master binary trees, binary search trees, and traversal techniques (in-order, pre-order, post-order).
- Practice: lowest common ancestor, bottom view, zigzag level traversal, diameter of tree.
- Graphs:
- Learn BFS, DFS, cycle detection, topological sort, Dijkstra’s algorithm, minimum spanning trees.
- Practice: number of islands, cycle detection in directed/undirected graphs, topological sort.
- Focus more on medium difficulty problems.
Week 8: Dynamic Programming (DP)
- DP is a technique, not an algorithm; second most frequent topic after graphs.
- Types: memoization and tabulation.
- Patterns: DP on subsequences, strings, 2D arrays, stocks.
- Practice 3-4 problems per pattern.
- Approach: start with recursive solution, identify overlapping subproblems, convert to memoization, then tabulation.
Phase 3: System Design and Mock Interviews (Days 61-90)
Week 9: Low-Level Design (LLD)
- Focus on object-oriented programming concepts: encapsulation, inheritance, polymorphism, abstraction.
- Learn design patterns: creational, structural, behavioral.
- Understand SOLID principles.
- Practice drawing UML diagrams and designing systems like parking lot, library, vending machine.
- Emphasize thinking about scalability, not rote memorization.
Week 10: High-Level Design (HLD)
- Study functional and non-functional requirements.
- Learn components: rate limiting, API gateways, load balancers, databases, CDN.
- Understand scaling: horizontal vs. vertical scaling, sharding.
- Practice designing systems like notification systems, chat systems, tiny URL.
- Always clarify requirements and scope before designing.
Week 11: Mock Interviews and Behavioral Questions
- Behavioral questions assess personality and working style (e.g., Amazon’s bar raiser, Google’s googliness).
- Use STAR method for answers: Situation, Task, Action, Result.
- Practice timed mock interviews: 45 minutes for DSA problem + 45 minutes for system design problem weekly.
- Consistent timed practice to simulate real interview conditions.
Week 12: Revision Strategies
- Focus on revising patterns rather than re-learning everything.
- Solve 1-2 problems per pattern to reinforce concepts.
- For system design, directly solve problems focusing on requirements, relationships, scaling, caching.
- Keep revising behavioral questions.
- Emphasize that revision is critical to retain knowledge.
Key Lessons and Methodology
- Consistent Practice: Daily, structured study and problem-solving.
- Deep Understanding: Implement data structures from scratch; understand internal workings.
- Pattern Recognition: Identify problem-solving patterns instead of memorizing solutions.
- Balanced Preparation: Equal focus on data structures, system design, and behavioral questions.
- Timed Practice: Simulate interview conditions with timed problem-solving.
- Revision: Regularly revisit and practice key patterns and system design concepts.
- Behavioral Preparation: Use STAR format and be authentic.
Speakers / Sources
- The video features a single primary speaker (likely the content creator or instructor) who guides through the roadmap and explains concepts, strategies, and problem examples.
- No other speakers or external sources are explicitly mentioned.
End of Summary
Category
Educational
