Professional
Software Interview Prep: Coding and Problem Solving
This course is a rapid intensive program designed to bridge the gap between academic computer science theory and the practical demands of industry coding interviews. We move beyond rote memorization by rigorously focusing on underlying algorithmic patterns. By the end of this course, students will possess the skills to deconstruct unseen problems, identify the optimal pattern, and implement bug-free, optimized code within the standard 30-45 minute interview timeframe.
Bridge the gap between academic computer science theory and the practical demands of industry coding interviews
What they'll walk away with
- Prepare for the software interview in FAANG companies
- Pattern Mastery: Master the Core Algorithmic Patterns, including Sliding Window, Two Pointers, DFS/BFS, and Dynamic Programming, ensuring proper application identification.
- Interview Readiness: Successfully solve the "Blind 75," a curated set of 75 high-frequency interview questions from top-tier tech companies.
- Code Optimization: Systematically analyze and articulate the Time and Space complexity (Big O notation) for every implemented solution.
- Effective Communication: Simulate real interview conditions and refine technical communication skills through weekly, structured mock sessions.
Curriculum
Learn algorithmic problem solving and system design
The Linear Foundation
- Arrays & Hashing. Hash Maps vs. Arrays. Prefix Sums. Complexity Analysis
- Two pointers. • Shrinking windows • Meeting in the middle • Handling sorted arrays
- Sliding Window. • Fixed vs. Dynamic Windows • Tracking window state • Substrings vs. Subsequences
- Fast & Slow Pointers (Cycle Detection). • Floyd’s Cycle Algorithm • Mock Interview
Recursion & Linear Structures
- In-Place Reversal & Cyclic Sort • Reversing Links safely • Sorting • Utilizing Dummy Nodes
- Stacks & Queues • Monotonic Stacks • Parentheses Matching • Queue implementation techniques
- Binary Search (Modified) • Search Spaces (beyond arrays) • Handling Rotated Arrays • Advanced Boundary Checks
- Bitwise XOR & Mock Review • Practical Bit manipulation tricks • Mock Interview Session #2
Trees, Heaps, and Graphs
- Tree DFS & BFS • Recursive vs. Iterative Traversal • Level Order Traversal • Validating Binary Search Trees
- Heaps (Priority Queue) & Top 'K' Elements • Min-Heap vs. Max-Heap • Efficiently finding "Best" elements
- Subsets & Backtracking • Understanding Decision Trees • Constraint Pruning • Permutations vs. Combinations strategies
- Graphs & Tries • Adjacency List Implementation • Mock Interview Session #3 • Prefix Trees (Trie) for string operations
Advanced Optimization
- Advanced Graphs (Topological Sort) • Directed Acyclic Graphs (DAGs) • Union Find (Disjoint Set) • Kahn’s Algorithm for ordering
- Merge Intervals & Greedy • Pre-sorting intervals • Techniques for Merging Overlaps • Principles of Local Optimization
- Dynamic Programming (1D & Knapsack) • Memoization vs. Tabulation • The "Unbounded Knapsack" • DP applied to Palindromic problems
- Final Mocks & Review • Full Mock Loop (45 mins) • System Design High-Level Overview (Optional) • Final Retrospective
Skills covered
What you'll need
- Expert proficiency in the Python programming language.
- Solid understanding of fundamental data structures and algorithms (e.g., Arrays, Lists, Dictionaries/Hashmaps, Sorting, Trees).
- A reliable computing environment and high-speed internet access are required for online participation.
Keep going
Other courses on this track
Most learners move through two or three courses as they grow.
Try Software Interview Prep: Coding and Problem Solving for free.
One live demo class, no commitment. Rates for this course are published per class.