Decode the Coding Interview in Python: Real-World Examples Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Introduction & Setup
Estimated time: 1 hour
- Overview of coding interviews
- Python setup for coding challenges
- Understanding big-O notation
- Setting expectations for technical interviews
Module 2: Arrays & Strings
Estimated time: 3 hours
- Sliding window technique
- Two pointers pattern
- In-place array modifications
- String manipulation and traversal
Module 3: Linked Lists
Estimated time: 2.5 hours
- Singly and doubly linked list structures
- Cycle detection algorithms
- Reversing a linked list
- Merging linked lists
Module 4: Stacks & Queues
Estimated time: 2.5 hours
- Stack implementation in Python
- Queue using two stacks
- Monotonic stack patterns
- Valid parentheses and related problems
Module 5: Trees & Graphs
Estimated time: 4 hours
- Binary tree structures and traversal
- Depth-first search (DFS)
- Breadth-first search (BFS)
- Graph representation and common patterns
Module 6: Recursion & Backtracking
Estimated time: 3 hours
- Designing base cases
- Recursive call flow
- Permutations and combinations
- Backtracking with examples like Word Search
Module 7: Sorting & Searching
Estimated time: 2.5 hours
- Merge sort implementation
- Binary search variations
- Quickselect algorithm
- Searching in rotated sorted arrays
Module 8: Dynamic Programming
Estimated time: 4 hours
- Memoization vs tabulation
- State transition logic
- Overlapping subproblems identification
- Solving problems like Climbing Stairs and 0/1 Knapsack
Module 9: Mock Interview Problems
Estimated time: 3 hours
- Comprehensive problem solving across data structures
- FAANG-style coding challenges
- Timed problem practice
- End-to-end solution walkthroughs
Prerequisites
- Familiarity with basic Python syntax
- Understanding of basic programming concepts (variables, loops, functions)
- Basic knowledge of data types and control structures
What You'll Be Able to Do After
- Master essential data structures and algorithms in Python
- Solve real-world coding interview problems efficiently
- Apply advanced techniques like recursion and dynamic programming
- Analyze time and space complexity accurately
- Write clean, testable, and scalable code for technical interviews