How to prepare for coding interviews in one month

Preparing for coding interviews at technology companies can be stressful. With many people competing for a single role, only a few secure the job. While multiple factors influence your selection, thorough preparation is one you can control. A well-structured plan can minimize your preparation time and increase your chances of success. This comprehensive guide outlines a one-month study plan divided into four weeks to help you systematically approach your coding interview preparation.

Week 1: Brush up on the basics#

A strong foundation is critical for solving complex coding challenges. This week, focus on understanding the interview process, revisiting core concepts, and getting comfortable with basic data structures. By the end of this week, you should have a solid grasp of the fundamental concepts that will serve as building blocks for the rest of your preparation.

Day 1: Understand the interview process#

Before you start preparing for the interview, it is important to research the company you’re applying to. Each company has its interview process, so it’s better to familiarize yourself with the typical structure, such as coding rounds, system design interviews, and behavioral interviews, to avoid last-minute surprises. Additionally, reading interview experiences from previous candidates can provide valuable insights into what to expect, and the do’s and don’ts. Platforms like Glassdoor and LinkedIn offer honest reviews and detailed accounts of interview processes, which can be incredibly helpful.

Days 2–4: Language proficiency and problem-solving basics#

• Reinforce language fundamentals: It’s essential to choose the programming language you’re most comfortable with—Python, Java, JavaScript, or C++—and stick with it throughout your preparation and the interview. Now isn’t the time to learn a new language; instead, focus on refining your proficiency. Reacquaint yourself with the syntax, data types, control flow, and OOP concepts of your chosen language. Additionally, practice writing clean, efficient code to strengthen your problem-solving skills in the language you’ve selected.

• Grasp problem-solving techniques: Technical interviews are all about coding and designing logic. Begin with simple logic puzzles and algorithmic thinking exercises to sharpen your problem-solving skills.

• Understand time and space complexity: Learn about Big O notation and how to analyze the efficiency of algorithms and data structures. This is very important as it will help you distinguish from all the candidates. Refer to the Big O cheat sheet for a quick refresher on this fundamental concept.

Days 5–7: Basic data structures#

Now that the fundamentals are out of the way, it’s time to start preparing for what will be asked during the interviews. It’s always best to start with the basic data structures and refresh your memory. Data structures are the building blocks for organizing and storing data efficiently. Here is a list of some basic data structures to start from:

• Arrays: Understand single-dimensional arrays. Focus on array operations like searching, sorting, insertion, and deletion and their associated time and space complexities.

• Linked lists: Grasp the concept of nodes and pointers and understand different types of linked lists, such as singly linked lists and doubly linked lists. Practice common operations, including traversal, insertion, and deletion.

• Stacks: Understand the Last In, First Out (LIFO) principle and how stacks are implemented using arrays and linked lists. Explore their use cases, such as function calls and expression evaluation.

• Queues: Understand the First In, First Out (FIFO) principle and how queues are implemented using arrays and linked lists. Learn about their use cases, such as breadth-first search and task scheduling.

• Trees: Explore different types of trees, including binary and binary search trees. Study various traversal methods, such as in-order, pre-order, and post-order traversal, and understand tree operations like insertion, deletion, and search.

For a quick yet detailed overview, you can refer to the data structures cheat sheet. However, if you’re looking for a more comprehensive and in-depth exploration, you can explore the Data Structures with Generic Types course, available in Python, Java, and C++.

Week 2: Dive deeper into data structures and algorithms#

Building upon the foundation laid in the last week, week 2 focuses on deepening your understanding of data structures and algorithms. Mastering these concepts is important for tackling complex coding challenges and showcasing your problem-solving abilities during interviews. By the end of this week, you should have a strong grasp of advanced data structures and fundamental algorithms, enabling you to approach coding problems confidently.

Days 8–10: Advanced data structures#

With a solid understanding of basic data structures, it’s time to explore more complex ones. These data structures are often used in solving hard problems and can significantly impact the efficiency of your solutions. A few of them include the following:

• Dynamic arrays: Understand the concept of dynamic arrays (or resizable arrays) and how they differ from traditional arrays. Focus on operations like appending, inserting, and deleting elements.

• Circular linked lists: Explore circular linked lists, and circular doubly linked lists, their structure, and use cases. Implement basic operations like insertion, deletion, and traversal.

• Heaps: Grasp the concept of heaps (max and min heaps), their properties, and implementations using arrays. Understand heap operations like insertion, deletion, and finding the maximum/minimum element. 

• Hash tables: Deepen your understanding of hash tables, collision resolution techniques, and their applications. Implement a hash table using an array and linked lists.

• Tries: Explore the tries data structure in detail, including their implementation and use cases. Practice building tries and performing operations like insertion, search, and deletion.

• Graphs: Understand the concept of graphs, their representations (adjacency matrix, adjacency list), and basic terminologies (vertices, edges, directed/undirected graphs, weighted/unweighted graphs).

Refer to the data structures cheat sheet for a more in-depth understanding of these advanced data structures concepts.

Days 10–12: Core algorithms#

This phase is crucial for developing your problem-solving skills and algorithmic thinking. Focus on understanding the core algorithms and their applications. Here are some fundamental algorithms to study:

• Sorting algorithms: Different methods to arrange data in a specific order, such as Quick Sort, Merge Sort, and Bubble Sort.

• Searching algorithms: Techniques for finding specific elements within a dataset, such as Binary Search, Depth-First Search (DFS), and Breadth-First Search (BFS).

• Graph algorithms: Algorithms for solving problems on graph structures, such as Dijkstra’s and Bellman-Ford algorithms.

• Recursion: Understand the principles of recursion and practice problems like generating permutations and solving the Tower of Hanoi.

• Dynamic programming: A technique for solving complex problems by breaking them into simpler, overlapping subproblems. Practice problems like the knapsack problem and the longest common subsequence. Refer to the dynamic programming cheat sheet for a comprehensive overview and additional practice problems.

• Greedy algorithms: Algorithms that make locally optimal choices at each step. Examples include the activity selection problem and Huffman coding.

• Backtracking: A systematic approach to explore all possible solutions to a problem. Examples include solving Sudoku puzzles and generating permutations.

Depending on your language preference, you can explore the Mastering Algorithms for Problem Solving course, available in Python, C++, and Java.

Days 13–14: Practice problem-solving#

By now, you should have a strong understanding of the fundamentals of data structures and algorithms. It’s time to elevate your preparation and test your understanding by practicing real-world interview problems.

Since we are on a time crunch, instead of grinding LeetCode randomly, work on problems using coding interview patterns. Almost all questions in a coding interview are built on patterns that serve as a blueprint for solving related problems. Learning the 26 core patterns that comprise nearly every technical interview question will allow you to prepare more comprehensively and effectively.

If you're unfamiliar with patterns, refer to the 'Coding Interviews LeetCode Patterns' for an overview of coding patterns and the seven most popular ones every software engineer should know.

Week 3: Object-oriented design and system design#

Week 3 focuses on higher-level design concepts important for solving system design and object-oriented programming questions often encountered in coding interviews. These questions are usually asked in the last rounds of your coding interviews.

Days 15–17: Object-oriented design principles#

Object-oriented design involves creating systems using objects and classes, focusing on principles like encapsulation, inheritance, and polymorphism. Interviewers often ask candidates to design systems to assess their ability to handle complexity and design scalable solutions. The CS101 cheat sheet can refresh your knowledge of OOP principles.

The OOD interview will primarily measure two abilities:

• Can you design a component that successfully interacts with other components in the system?

• Can you use design patterns to create this component efficiently?

To further enhance your skills, practice designing systems and implementing design patterns in various projects. Continuous practice will solidify your understanding and prepare you for your upcoming interviews.

Days 18–20: System design fundamentals#

System design interviews can be intimidating, especially since they are typically reserved for top-tier tech companies like Meta, Google, Amazon, and Netflix. These interviews assess your ability to architect scalable and reliable systems, which are critical skills for these positions. You must expect to tackle questions that involve designing large-scale systems, such as a URL shortener or a load balancer. In addition to system architecture, it’s vital to understand database schemas, normalization, indexing, and query optimization. Educative offers a comprehensive Deep Dive into System Design Interview course that prepares candidates effectively for system design interviews.

Week 4: Practice problems and mock interviews#

In the final week, you should focus on practicing coding problems and participating in mock interviews to simulate the real interview environment. This intensive practice will help reinforce the concepts you’ve learned over the past three weeks and build your confidence.

Days 22–24: Practice coding problems#

Set aside dedicated time each day to tackle multiple coding problems, focusing on medium-level challenges that closely simulate real interview scenarios. Time your sessions to simulate the pressure of an actual interview, aiming to complete each session within the typical 30–45 minute timeframe, which usually includes around three questions. Additionally, analyze the time and space efficiency of your solutions to enhance your code’s performance. Engaging with community groups can provide insights into different approaches to problem-solving.

You can enhance your preparation by working through a curated list of popular problems from Educative, featuring a range of coding patterns and difficulty levels that companies often ask in interviews. Depending on your preference, you can choose from the following tailored lists:

• Educative-99: This is a meticulously curated collection of 99 LeetCode problems designed to comprehensively cover all 26 essential coding patterns. The problems are carefully selected to span various difficulty levels, ensuring a well-rounded preparation experience.

• Blind 75: It is a curated list of 75 LeetCode problems identified as high-frequency interview questions, which serve as a focused study plan for aspiring software engineers, helping them efficiently prepare for coding challenges.

Days 25–27: Mock interviews#

To gain real-world interview experience, dedicate these days to participating in mock interviews. Here’s how to maximize this practice:

1. Select a platform: Use AI-powered mock interview platforms like Educative that simulate real interview environments.

2. Focus on key areas: Tailor your mock interviews to cover essential areas such as coding patterns, system design, and object-oriented design (OOD) interviews.

3. Company-specific preparation: If you have target companies in mind, customize your practice sessions to reflect the types of questions these companies typically ask, such as those from Meta, Apple, or Netflix.

4. Review your performance: After each mock interview, review your performance. Analyze your responses, identify areas for improvement, and adjust your preparation strategy accordingly.

5. Seek feedback: If possible, gather feedback from peers or mentors to gain additional insights on your interview technique and areas where you can improve.

You can see a list of a few AI-powered interviewers available at Educative:

Day 28: Final review and relaxation#

Take some time to review key concepts, data structures, and algorithms. Focus on areas where you feel less confident and ensure you understand them well. You may want to revise these concepts by reviewing the cheat sheets in this blog.

Additionally, it’s important to relax before the actual interview. Ensure you get a good night’s sleep, eat well, and engage in activities that help you relax. Being well-rested will help you perform better during the interview.

Conclusion#

Preparing for coding interviews at tech companies requires dedication, discipline, and a structured approach. Following this one-month study plan, you can systematically build your knowledge and skills, ensuring you’re well-prepared for your next interview. Remember, consistency is key—practice regularly, review your mistakes, and seek feedback to improve continuously.

You’ve got this—good luck and happy coding!