Google coding interviews on Data structure and Algorithms from Udemy

What's inside

Syllabus

Introduction

Array Data structure

Array Theory

Test your knowledge in Array Data structure

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers arrays and linked lists, which are fundamental data structures used in software development and computer science

Includes frequently asked questions in Google and other FAANG companies, which can help learners prepare for technical interviews

Explores time complexity, which is a core concept for understanding the performance of algorithms and data structures

Teaches algorithms for cycle detection and reversing linked lists, which are common tasks in software engineering

Explores the 'full sum problem,' which may be relevant to dynamic programming and algorithm design

Reviews summary

Arrays and linked lists interview prep

According to learners, this course offers a solid introduction to Arrays and Linked Lists, focusing on common coding interview problems often encountered in companies like Google and other FAANG members. Many students found the explanations clear and the coverage of basic concepts like cycle detection and reversing linked lists particularly helpful. However, some reviewers noted that the course primarily covers fundamental concepts and may require additional resources or more advanced study for comprehensive interview preparation, indicating it's a good starting point rather than an all-encompassing guide.

Only covers Arrays and Linked Lists.

"Note that this course strictly focuses on Arrays and Linked Lists as stated in the title."

"This is only Season 1 covering two data structures, so expect to need other resources for topics like trees, graphs, etc."

"The course syllabus accurately reflects the limited scope of just Arrays and Linked Lists."

Provides a good starting point for basics.

"This course is excellent for getting a handle on the fundamentals of Arrays and Linked Lists."

"It's a great place to start if you are new to these data structures or need a refresher on basics."

"I got a solid foundation on the core concepts from this course."

Focuses on practical coding interview questions.

"The problems covered, like cycle detection and reverse linked list, are exactly the types I've seen in interviews."

"Solving these specific problems helped me understand how to apply the data structures effectively."

"I found the focus on frequently asked questions in interviews to be highly relevant and useful."

Reviewers praise the instructor's clarity.

"The explanations for data structures and algorithms were very clear and easy to follow."

"The instructor explains the concepts in a way that is easy to grasp, even for complex topics."

"I really appreciate the clear way the lectures break down each problem and data structure."

Could benefit from more practice problems.

"While the lecture problems are good, I wish there were more practice problems provided for each topic."

"More coding exercises would help solidify the concepts much better."

"The course could be improved by adding a dedicated set of practice questions after each section."

May not be sufficient for advanced prep.

"While the basics are covered well, the course lacks the depth needed for higher-level interview questions."

"Could use more advanced problems and optimization techniques beyond the fundamentals taught here."

"I felt that after finishing the course, I still needed to seek out more challenging problems elsewhere."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Google coding interviews on Data structure and Algorithms with these activities:

Review Array Fundamentals

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Solidify your understanding of array fundamentals before diving into more complex data structures and algorithms.

Browse courses on Arrays

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Review array concepts such as indexing, slicing, and common operations.
Practice implementing basic array algorithms like searching and sorting.

Review 'Cracking the Coding Interview'

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Supplement your learning with a comprehensive guide to coding interviews.

View Cracking the Coding Interview: 189 Programming... on Amazon

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Read the chapters on arrays and linked lists.
Solve the practice problems at the end of each chapter.
Review the solutions and explanations.

LeetCode Array Problems

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Sharpen your array manipulation skills by solving a variety of LeetCode problems.

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Select 5-10 array-related problems on LeetCode with varying difficulty levels.
Implement solutions in your preferred programming language.
Analyze the time and space complexity of your solutions.

Four other activities

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Implement Linked List Operations

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Reinforce your understanding of linked lists by implementing common operations from scratch.

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Implement insertion, deletion, and traversal operations for singly linked lists.
Implement cycle detection and reversal algorithms.
Test your implementations thoroughly with various test cases.

Create a Data Structure Cheat Sheet

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Consolidate your knowledge by creating a cheat sheet summarizing key concepts and operations for arrays and linked lists.

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Summarize the key properties and operations of arrays and linked lists.
Include diagrams and examples to illustrate the concepts.
Organize the cheat sheet for easy reference.

Review 'Introduction to Algorithms'

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Deepen your understanding of algorithms with a classic textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Read the sections on arrays and linked lists.
Work through the exercises and problems.
Consult the book as a reference for more in-depth explanations.

Implement a Custom Data Structure

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Deepen your understanding of data structures by implementing a custom data structure from scratch.

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Choose a data structure (e.g., hash table, binary search tree) not explicitly covered in the course.
Design the data structure's API and internal representation.
Implement the data structure and its core operations.
Write unit tests to ensure the data structure's correctness.

Career center

Learners who complete Google coding interviews on Data structure and Algorithms will develop knowledge and skills that may be useful to these careers:

Algorithm Developer

An Algorithm Developer designs and implements computer algorithms to solve specific problems. This course helps build the foundational knowledge required for algorithm development, particularly through its focus on data structures and algorithms. The course's exploration of arrays, linked lists, and related algorithms provides a solid base for understanding more complex algorithmic concepts. The focus on time complexity analysis provides skills for optimizing algorithm performance. Aspiring Algorithm Developers benefit from the practice with interview questions from top tech companies, which simulates the challenges encountered in algorithm design and implementation. The course may be useful to anyone planning a career as an Algorithm Developer.

See salaries and explore the career path for Algorithm Developer

Software Engineer

A Software Engineer designs, develops, tests, and maintains software systems. This course helps those aspiring to become Software Engineers by focusing on data structures and algorithms, essential components for efficient and effective code. The course's coverage of arrays and linked lists builds a foundation for understanding more complex data structures encountered in software development. Furthermore, the practice with frequently asked questions from Google and other FAANG companies makes one better prepared for technical interviews and on-the-job problem-solving. The specific modules on linked list manipulation, such as reversing a linked list and cycle detection, are directly applicable to real-world coding scenarios. This course may be useful for anyone planning a career as a Software Engineer.

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Technical Lead

A Technical Lead guides and mentors a team of developers, often requiring advanced technical expertise. This course helps Technical Leads by strengthening their understanding of data structures and algorithms, which are essential for providing technical guidance and making informed design decisions. The course's coverage of arrays and linked lists provides a foundation for understanding how data is organized and manipulated. Technical Leads can apply the concepts of time complexity to assess performance and optimize solutions. The problem-solving practice would also benefit Technical Leads, who must frequently address complex technical challenges. This course may be useful for anyone planning a career as a Technical Lead.

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Backend Developer

A Backend Developer focuses on building and maintaining the server-side logic and databases that power web applications. This course may be useful to Backend Developers by providing expertise in data structures. This knowledge helps in designing efficient and scalable backend systems. The course's coverage of data structures like arrays and linked lists provides a foundation for understanding how data is stored and accessed in databases and other backend components. In addition, the focus on time complexity could be useful for optimizing database queries and other performance-critical operations. This course may improve one's ability to solve common backend challenges such as data storage, retrieval, and manipulation. This course may be useful for anyone planning a career as a Backend Developer.

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Full-Stack Developer

A Full Stack Developer works on both the front-end and back-end of web applications. This course helps Full Stack Developers by strengthening their understanding of data structures and algorithms, which are crucial for both front-end and back-end development. The course's exploration of arrays and linked lists provides a foundation for efficient data handling and manipulation. The practice with interview questions from Google and other FAANG companies may prepare one for technical interviews and on-the-job problem-solving. The course may also be useful for Full Stack Developers as they optimize application performance. This course may be useful for anyone planning a career as a Full Stack Developer.

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Game Developer

A Game Developer designs and develops video games. This course helps Game Developers by improving their understanding of data structures and algorithms, which are essential for game development. The course's exploration of arrays and linked lists provides a foundation for efficient data management in game engines. The problem-solving practice may also benefit Game Developers, who often encounter complex challenges in game design and implementation. Learning about time complexity provides insight when designing solutions for performance-critical tasks in game development. This course may be useful for anyone planning a career as a Game Developer.

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Data Scientist

A Data Scientist analyzes data to extract meaningful insights and inform decision-making, often requiring proficiency in data structures and algorithms. The array and linked list concepts taught in this course build a foundation for understanding how data is organized and manipulated. This understanding is crucial for efficiently processing and analyzing large datasets. This course's emphasis on time complexity also provides skills in writing algorithms that scale well. Further, the course's content could be helpful for aspiring Data Scientists as they seek to optimize data processing pipelines and develop effective analytical models. The course may be useful for those planning a career as a Data Scientist.

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Mobile App Developer

A Mobile App Developer designs and develops applications for mobile devices. An understanding of data structures may be useful to Mobile App Developers, as it helps them optimize app performance. This course can help Mobile App Developers by improving their understanding of data structures and algorithms, which are crucial for efficient data handling in mobile apps. The course's coverage of arrays and linked lists provides a foundation for understanding how data is organized and manipulated. The focus on time complexity also helps optimize app performance. This course may be useful for anyone planning a career as a Mobile App Developer.

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Software Development Engineer in Test

A Software Development Engineer in Test (SDET) designs and implements tests to ensure software quality. This course helps SDETs by deepening their understanding of data structures and algorithms, which are essential for writing effective test cases and identifying potential bugs. The course's coverage of arrays and linked lists provides a foundation for understanding how data is stored and manipulated within the software. The focus on time complexity also helps SDETs write tests that can identify performance bottlenecks. This course may be useful for anyone planning a career as a Software Development Engineer in Test.

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Embedded Systems Engineer

An Embedded Systems Engineer designs, develops, and tests software for embedded systems, which often have limited resources. This course helps Embedded Systems Engineers by strengthening their understanding of data structures and algorithms, to develop resource-efficient code. The course's coverage of arrays and linked lists provides a foundation for efficient data management in embedded systems. The focus on time complexity assists in writing code that minimizes memory usage and execution time. The knowledge on linked lists and their manipulations as taught in this course builds a base for managing dynamic memory allocation within embedded systems. The course may be useful for anyone planning a career as an Embedded Systems Engineer.

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Data Analyst

A Data Analyst collects, cleans, and analyzes data to identify trends and insights. This course may be useful to Data Analysts by improving their understanding of data structures, which is essential for efficient data manipulation and analysis. The course's coverage of arrays and linked lists provides a foundation for understanding how data is organized and stored. This can lead to better data processing and analysis techniques. The course may also cover data analysis algorithms, which could be useful for extracting insights from data. This course may be useful for anyone planning a career as a Data Analyst.

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Quantitative Analyst

A Quantitative Analyst, often requiring an advanced degree, uses mathematical and statistical methods to solve financial problems. This course may be useful to Quantitative Analysts by providing a solid foundation in data structures and algorithms, which are often used in financial modeling and analysis. The course's exploration of arrays and linked lists provides a foundation for understanding how data is organized and manipulated. The focus on time complexity also helps optimize the performance of quantitative models. This can be helpful for Quantitative Analysts when analyzing large datasets and developing complex financial algorithms. This course may be useful for anyone planning a career as a Quantitative Analyst.

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Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. An understanding of data structures may be useful to Machine Learning Engineers, particularly in algorithm optimization and data preprocessing. While this course's focus is not directly on machine learning algorithms, it can help Machine Learning Engineers better understand how data is organized and manipulated. This can improve the efficiency of machine learning pipelines. The course may also be useful for Machine Learning Engineers as they seek to optimize model performance. This course may be useful for anyone planning a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Database Administrator

A Database Administrator manages and maintains databases to ensure data integrity and availability. This course may be useful to Database Administrators by providing an understanding of data structures. The course's coverage of data structures such as arrays and linked lists helps Database Administrators better understand how data is organized in databases. While this course doesn't focus on database-specific technologies, it may still be helpful to Database Administrators as they optimize database performance and troubleshoot data-related issues. This course may be useful for anyone planning a career as a Database Administrator.

See salaries and explore the career path for Database Administrator

DevOps Engineer

A DevOps Engineer automates and streamlines the software development lifecycle. While not directly related to the daily tasks of a DevOps Engineer, this course may still be useful. This course's exploration of data structures and algorithms may help analyze and optimize the tools used in development and deployment pipelines. The course's content may be useful as DevOps Engineers seek to streamline processes. A DevOps Engineer can utilize efficient algorithms to automate tasks. The course may be useful for anyone planning a career as a DevOps Engineer.

See salaries and explore the career path for DevOps Engineer

Google coding interviews on Data structure and Algorithms

What's inside

Syllabus

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Reviews summary

Arrays and linked lists interview prep

Activities

Career center

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