How we do programming patterns differently

 

Our 'Grokking the Coding Interview Patterns' series helps you understand the essence of each pattern through hands-on learning. Interactive quizzes, projects, and playgrounds simulate real interview scenarios, ensuring you're not just learning but applying.

Our courses aim to streamline the preparation process by enabling candidates to tackle many problems with a single pattern. You can reduce the need for exhaustive problem-solving and the risk of burnout by focusing on the underlying patterns behind coding questions. This approach has proven effective, helping you land jobs at top tech companies like Google, Facebook, Amazon, and Microsoft. It is a practical guide to acing interviews.

 

The approach emphasizes a structured and efficient preparation method, allowing candidates to approach coding interviews confidently and improve performance.
 

No setup woes. No toggling between platforms. Our highly interactive platform is designed to keep you focused and immersed in learning, mimicking the environment you'll face during interviews.

 

Whether trying to understand sliding windows, two pointers, matrix traversal, or merge intervals, our curriculum is crafted by industry experts to guide you from the basics to advanced strategies seamlessly.

​

Common patterns to ace any coding interview question 

​

1. Sliding window technique 

The sliding window pattern optimizes array and string-related problems by creating a movable “window” over the dataset, which can adjust in size. This technique is ideal for problems involving contiguous subarrays or sublists and is commonly used to find maximum subarray sums, or the longest substring with distinct characters. Its main advantages are reducing time complexity from O(n^2) to O(n) and its adaptability to various problems, although it can be initially complex to understand and is specific to contiguous data structures.

 2. Two pointers

The two pointers technique optimizes algorithms by using two pointers to iterate through data structures like arrays or linked lists, eliminating the need for inefficient nested loops and reducing time complexity from O(n²) to O(n). This method is especially effective with ordered data structures to find elements meeting specific conditions. 

​

 3. Reverse linked list 

The in-place reversal of a linked list pattern reverses nodes by manipulating pointers directly, offering memory efficiency (O(1) space complexity) but requiring careful pointer handling and initial practice.

​

 4. Backtracking

​

Backtracking is an algorithmic technique for exploring all potential configurations of a search space, ideal for combinatorial problems and puzzles. It guarantees completeness but can be time-intensive without optimizations.

​

 5. Modified binary search 

​

The modified binary search pattern efficiently handles searches in sorted arrays by adapting classic binary search to prevent integer overflow and optimize searching boundaries, enhancing both efficiency and versatility.

​

Let's make cracking the coding interview easier

 

Make your coding skills as dynamic and adaptable as the tech landscape itself. With our guidance, you won't just prepare for your next coding interview. You'll also be preparing for a thriving career in technology.

​

Frequently Asked Questions (FAQs)

​

1. Is backtracking important for an interview? 

By familiarizing themselves with the common framework of backtracking questions, methodically addressing them, and recognizing the types of problems suited to this technique, candidates can improve their problem-solving capabilities to excel in technical interviews.

​

2. How to print the level order traversal of a tree?

The primary concept behind level order traversal is to visit all nodes on a given level before advancing to a higher level. This traversal can be executed through various methods:

 

• A basic approach, which determines the tree's height and traverses and prints the nodes level by level.

• A more efficient method, which utilizes a queue to facilitate the traversal process.

 

3. How to find the longest palindrome in a string?

• Declare and initialize an integer array, sort it in ascending order, find the largest element, and then reverse it.

• Check if the reversed element is a palindrome and print the result.