Decode the Coding Interview in Java: Real-World Examples Course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview: This intensive course is designed to prepare Java developers for technical interviews at top-tier companies. With a hands-on, code-first approach, it covers essential data structures, algorithms, and problem-solving patterns used in real-world coding interviews. Structured across 8 modules, the course spans approximately 8 weeks with a recommended commitment of 6–8 hours per week. Each module combines conceptual learning with practical coding challenges in Java, culminating in mock interviews and a capstone simulation. The text-and-code format emphasizes active practice over passive viewing, making it ideal for self-driven learners aiming to master algorithmic thinking and coding efficiency.

Module 1: Java Foundations & Problem Solving

Estimated time: 6 hours

  • Java syntax refresher
  • Java Collections Framework overview
  • Time and space complexity analysis
  • Implementing and analyzing sorting and searching algorithms

Module 2: Arrays & Strings

Estimated time: 6 hours

  • Two-pointer technique
  • Sliding window pattern
  • Frequency counting methods
  • Solving 'Longest Substring Without Repeating Characters' and 'Array Pair Sum'

Module 3: Linked Lists & Stacks/Queues

Estimated time: 6 hours

  • Singly and doubly linked list implementations
  • Stack and queue operations using Deque
  • Hands-on: Reverse a Linked List
  • Hands-on: Valid Parentheses checker

Module 4: Trees & Graphs

Estimated time: 6 hours

  • Binary tree traversals (inorder, preorder, postorder)
  • Binary Search Tree operations
  • Breadth-First Search (BFS) and Depth-First Search (DFS) on graphs
  • Implementing 'Lowest Common Ancestor' and 'Graph Cycle Detection'

Module 5: Recursion & Backtracking

Estimated time: 6 hours

  • Recursive patterns and call stack mechanics
  • Pruning in recursive solutions
  • Backtracking techniques
  • Solving 'N-Queens' and 'Permutations' using recursion in Java

Module 6: Dynamic Programming & Greedy

Estimated time: 6 hours

  • Memoization vs. tabulation
  • Identifying optimal substructure and overlapping subproblems
  • Greedy algorithm strategies
  • Solving 'Coin Change' and 'Longest Increasing Subsequence'

Module 7: Mock Interviews & Optimization

Estimated time: 6 hours

  • Simulated technical interview scenarios
  • Code optimization techniques
  • Space/time trade-offs
  • Interview etiquette and communication best practices

Module 8: Capstone Challenge

Estimated time: 8 hours

  • End-to-end coding interview simulation
  • Solving multi-problem challenges in timed conditions
  • System design primer for algorithm-focused roles

Prerequisites

  • Familiarity with basic Java syntax and object-oriented programming
  • Understanding of fundamental programming constructs (loops, conditionals, methods)
  • Basic knowledge of data structures like arrays and lists

What You'll Be Able to Do After

  • Master core data structures and algorithms in Java
  • Apply proven problem-solving patterns to coding challenges
  • Analyze time and space complexity using Big O notation
  • Write clean, efficient, and optimized Java code under time constraints
  • Approach technical interviews at top tech companies with confidence
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