Visão Geral
O curso Grokking the Coding Interview Patterns in JavaScript foi desenvolvido para ajudar desenvolvedores a dominar os padrões de resolução de problemas mais comuns em entrevistas técnicas, utilizando a linguagem JavaScript.
Durante o curso, o aluno aprenderá a identificar padrões recorrentes em problemas de lógica e algoritmos, aplicando soluções otimizadas e reutilizáveis — habilidades essenciais para se destacar em entrevistas de empresas como Google, Meta, Amazon, Microsoft e outras líderes de tecnologia.
Conteúdo Programatico
Module 1: Introduction to Interview Patterns
- Overview of coding interview formats and expectations
- Understanding the importance of problem-solving patterns
- Time and space complexity refresher
- Setting up the JavaScript environment for coding interviews
Module 2: Sliding Window Pattern
- Concept and applications of the sliding window technique
- Solving substring, subarray, and sequence problems
- Practice problems: maximum sum subarray, longest substring without repeating characters
Module 3: Two Pointers Pattern
- Introduction to pointer-based problem solving
- Fast and slow pointer techniques
- Common problems: pair sum, remove duplicates, linked list cycle detection
Module 4: Fast and Slow Pointers
- Understanding slow-fast traversal patterns
- Detecting cycles in linked lists and arrays
- Applications in palindrome and middle-element problems
Module 5: Merge Intervals Pattern
- Understanding interval overlapping and merging
- Sorting and merging intervals efficiently
- Practice problems: meeting rooms, employee free time, insert interval
Module 6: Cyclic Sort Pattern
- The cyclic sort approach for dealing with ordered numbers
- Finding missing, duplicate, and smallest positive numbers
- Pattern-based optimization techniques
Module 7: In-place Reversal of a Linked List
- In-place reversal technique explained
- Applications in reversing sublists and k-group reversals
- Linked list design interview problems
Module 8: Tree and Graph Traversal Patterns
- Depth-First Search (DFS) and Breadth-First Search (BFS) in JavaScript
- Recursion vs iterative traversal
- Solving binary tree and graph traversal problems
Module 9: Topological Sort and Subset Patterns
- Introduction to topological sorting
- Solving dependency and scheduling problems
- Subset, permutation, and combination generation using recursion and backtracking
Module 10: Dynamic Programming and Greedy Patterns
- Recognizing overlapping subproblems and optimal substructure
- Memoization and tabulation strategies
- Classic DP problems: knapsack, coin change, Fibonacci
- Applying greedy algorithms where appropriate
Module 11: Practice, Optimization, and Mock Interviews
- Applying multiple patterns in complex problems
- Mock interview sessions and whiteboard practice
- Optimization and debugging techniques
- Final capstone project: solving end-to-end coding problems