How to prepare for your first technical interview

Many software engineers dream of landing a job at a top-tier tech company like those in MAANG (Meta, Apple, Amazon, Netflix, Google). However, it’s a highly competitive field. Only 5 out of every 100 applicants are typically selected for preliminary screening; from there, only one out of five receives an offer. Standing out during the interview process is challenging, but with the right preparation, you can maximize your chances of success.

5 steps to master the technical interview process

A well-structured preparation plan is necessary for covering important topics and managing your time effectively during the interview. On the day of your interview, the last thing you want is to be surprised by unexpected questions. In this blog, we have prepared a comprehensive plan comprising 5 steps that can help you master the technical interview process in just a matter of a few weeks.

The 5 steps of mastering the technical interview process are as follows:

1. Solidify your programming language fundamentals

2. Review data structures and algorithms

3. Practice with data structures and algorithms

4. Practice with real-world coding interview problems

5. Object-oriented design and behavioral interviews

Solidify your programming language fundamentals

Before diving into complex algorithms and data structures, it’s important to have a solid grasp of your chosen programming language. At this step of the technical interview prep, you should revise the basics to ensure you’re well-prepared to solve the simple questions often posed at the beginning of an interview. Many technical interviews start with straightforward questions to assess your foundational knowledge and help ease your nerves. 

Your language fundamentals should be so ingrained that you can effortlessly perform basic tasks, freeing up mental energy for more challenging problems. It’s important to decide which language you want to use for the interview and stick with it during preparation and the interview itself. Now is not the time to learn a new programming language; choose the language you're most comfortable with.

Try practicing simple exercises in your chosen programming language, such as:

• String manipulation: Write a function to split a string by spaces.

• File parsing: Parse a simple CSV file and output the contents.

• 2D arrays: Declare a 2D array and fill it with values.

• File I/O: Read from a text file and write the output to another file.

• Command line arguments: Write a program to process and output command line arguments.

Practice resources

To solidify your foundation, Educative offers a variety of courses in different programming languages, perfect for brushing up on the basics. You can find Python, C++, Java, JavaScript, Go, and C# courses. These courses cover key concepts to help you practice fundamental questions.

By brushing up on skills using the selected course and practicing the exercises it provides, you’ll build a strong foundation in your chosen language, setting yourself up for success in more advanced interview stages.

Review data structures and algorithms

With your language fundamentals solidified, it’s time to revise data structures and algorithms. These are the backbone of technical interviews; a deep understanding of them is critical for solving complex coding challenges. At this step, you must focus on deeply understanding these fundamental concepts.

Key data structures to review

Data structures are the building blocks for organizing and storing data efficiently. Here are some essential data structures to learn:

• Arrays: Understand different array types, such as single-dimensional and multi-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, doubly linked lists, and circular 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 trees, binary search trees, AVL trees, and heaps. Study various traversal methods, such as in-order, pre-order, and post-order traversal, and understand tree operations like insertion, deletion, and search.

• Graphs: Understand graph representations, such as adjacency matrices and adjacency lists. Learn traversal algorithms like Depth-First Search (DFS) and Breadth-First Search (BFS), and shortest path algorithms like Dijkstra’s and Bellman-Ford algorithms.

• Hash tables: Learn about the concept of hashing and collision handling techniques. Also, learn about the use cases for hash tables, such as dictionaries and sets.

Important algorithms to master

Algorithms are step-by-step procedures for manipulating data and solving computational problems. Here are some fundamental algorithms to study:

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

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

• Graph algorithms: These are 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: It is a technique for solving complex problems by breaking them into simpler, overlapping subproblems. Practice problems like the knapsack problem and the longest common subsequence. For a comprehensive overview and additional practice problems, refer to the dynamic programming cheat sheet. Alternatively, you may learn through the complete dynamic programming course if you require more practice.

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

• Backtracking: It‘s a systematic approach to exploring all possible solutions to a problem. Examples include solving Sudoku puzzles and generating permutations.

Cheat sheets for a quick refresher

For a quick refresher or revision of key concepts, use the following cheat sheets:

•  Data Structures 101: It’s a concise overview of basic data structures and their operations.

•  Data Structures 201: This is an advanced guide to more complex data structures and their uses.

Algorithm analysis and practice

Understanding algorithm efficiency and applying your knowledge through practice is crucial. Focus on:

• Time and space complexity: Analyze algorithms’ performance using Big O notation. Refer to the  Big O cheat sheet to quickly recall the time and space complexities of various algorithms and data structures.

• Problem-solving techniques: Break down problems, identify patterns, and design effective algorithms.

Practice resources

Educative offers comprehensive data structures and algorithms courses tailored to various programming languages. These courses provide in-depth explanations and practical exercises to enhance your understanding.

For a refresher on data structures, review the following:

By the end of these two weeks, you should have a strong grasp of data structures and algorithms, preparing you for more complex challenges in your technical interviews.

Practice with data structures and algorithms

Now the technical interview prep should shift focus on applying the concepts learned in the previous step into practical application. The goal is to solidify your understanding and ensure you can implement these data structures and algorithms efficiently during an interview. You start by tackling various problems that require you to implement the data structures and algorithms you’ve reviewed. The practice will help you internalize these concepts and improve your problem-solving speed and accuracy.

Focus on practice

• Start simple: Begin with problems that align with the data structures and algorithms you’ve studied. Gradually increase the difficulty level.

• Time yourself: Simulate interview conditions by practicing under time constraints.

• Analyze your solutions: Evaluate your code’s time and space complexity and look for opportunities to optimize it.

• Review solutions: Analyze different approaches to solving a problem. Learn from others’ code and find alternative solutions on community forums such as the  Discuss forum provided by Educative.

Our hands-on “Data Structures for Coding Interviews” courses, available in Python, Java, C++, JavaScript, and C#, will help you review all the common data structures in detail.

To solve problems focusing on algorithms, review the following resources:

Common pitfalls and tips

• Avoid overcomplicating solutions: Keep your code clean and concise. Often, simpler solutions are more efficient.

• Test thoroughly: Write comprehensive test cases to ensure your code works correctly under various conditions.

• Explain your thought process: Practice articulating your reasoning during problem-solving. This is crucial for interviews.

You’ll develop the problem-solving skills and confidence needed to excel in technical interviews by dedicating ample time to practice.

Practice with real-world coding interview problems

By this stage, 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. 

Transitioning to real-world problems

• Time management: Timing your problem-solving sessions will simulate the pressure of an interview. Aim to complete each problem within the typical interview timeframe, which usually lasts 30–45 minutes and includes around 3 questions.

• Complexity analysis: Continuously analyze your solutions for time and space efficiency to improve your code’s performance. Engage with community groups to see how others are solving the problems.

• Identify common patterns: Instead of practicing problems 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. While daily LeetCode practice can keep your problem-solving skills sharp, 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, get an overview of what coding patterns are and the 7 most popular ones that every software engineer should know.

• Mock interviews: Gain real-world interview experience through  mock interviews. Applying the techniques mentioned in this blog during the mock interviews will give you the confidence and muscle memory needed to perform flawlessly. Platforms like Educative offer a range of mock interviews, allowing you to practice with various coding patterns and even improve your approach for specific companies like Meta, Apple, Netflix, and more.

During these mock interviews, pay close attention to the interviewer’s feedback. Use the insights provided to identify areas for improvement and refine your skills and overall interview strategy.

Practice resources

• Learn how to solve any possible coding interview problem with 26 coding patterns designed by the hiring managers at MAANG companies. Grokking Coding Interview Patterns is a popular course offered by Educative, which covers these patterns and problems that can be solved using them. It is available in six programming languages. 

• Try the accelerated preparation plans offered by Educative—Educative-77, and Educative-99 for even faster preparation. These are also available in multiple languages to help learners quickly understand the important concepts and patterns needed to excel in coding interviews. You can select any plan from the list below depending on your language preference and preparation time:

By leveraging these resources and focusing on real-world coding interview problems, you'll be well-equipped to handle the challenges of technical interviews and increase your chances of securing a job offer.

Object-oriented design and behavioral interviews

As you approach the end of your preparation plan, this last step focuses on two critical aspects of the technical interview process

• Object-oriented design (OOD)

• Behavioral interviews.

These areas are important as they evaluate your problem-solving approach, design skills, and cultural fit within a company. Let’s look at both one by one:

Object-oriented design (OOD)

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. For a refresher on OOP principles, refer to  Object-Oriented Programming (OOP)-CS101  cheat sheet.

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?

Mastering object-oriented design (OOD) principles is crucial for low-level design interviews. Focusing on various design patterns and their applications will significantly enhance your preparation. The “Grokking the Low-Level Design Interview using OOD Principles” course offered by Educative provides a structured approach to solving design problems using a bottom-up approach to effectively break down complex design challenges.

Behavioral Interviews

Behavioral interviews assess your soft skills, cultural fit, and how you handle various situations. They typically involve questions about past experiences, teamwork, leadership, conflict resolution, and problem-solving abilities. To excel in these interviews, follow these steps:

1. Understand the STAR method: Structure your answers using the situation, task, action, and result framework.

2. Practice common questions: Prepare for typical behavioral questions about teamwork, leadership, problem-solving, and handling challenges.

   1. Tell me about a time you faced a significant challenge at work. How did you handle it?

   2. Describe a situation where you had to work closely with a team. What was your role, and how did you contribute to the team’s success?

   3. Give an example of a time when you showed leadership skills.

   4. How do you handle tight deadlines or high-pressure situations?

3. Highlight achievements: Showcase your accomplishments and quantify your impact whenever possible.

4. Research the company: Understand the company’s culture and values to tailor your responses accordingly.

For a comprehensive breakdown of these steps, check out our detailed popular course offered by Educative:

Conclusion

Cracking the technical interview requires a comprehensive approach encompassing coding fundamentals, problem-solving abilities, and effective communication. Though the first technical interview can be intense, with our 5 steps structured plan, you can confidently navigate each stage. With your preparation plan in place, it’s time to implement it.

Start by setting a schedule and dedicating weekly time to focus on the topics and exercises outlined. Utilize the recommended resources to deepen your understanding, practice effectively, and before you know it, you’ll be smashing the technical interview process.

Don’t forget to engage in AI-powered mock interviews and seek feedback to refine your skills.

Good luck with your first technical interview!