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Data Structures Algorithms in Java – SECRETS to Ace LeetCode
Prerak Mehta
4.2
Based on 128 ratings
Prerak Mehta
Did you know that According to the U.S. Bureau of Labor and Statistics, developers will see job growth of 27% by 2024?
The problem is that everyone you know (your friends, family, professors, co-workers, etc) are LYING to you and most don’t even know it.
They tell you to…
Graduate from a "prestigious" university with an overpriced degree (which holds less weight than ever before)…
It’s too difficult to code
It’s too late to learn
You are not meant to code
This sounds pretty depressing, doesn’t it?
Read more
Did you know that According to the U.S. Bureau of Labor and Statistics, developers will see job growth of 27% by 2024?
The problem is that everyone you know (your friends, family, professors, co-workers, etc) are LYING to you and most don’t even know it.
They tell you to…
Graduate from a "prestigious" university with an overpriced degree (which holds less weight than ever before)…
It’s too difficult to code
It’s too late to learn
You are not meant to code
This sounds pretty depressing, doesn’t it?
Read more
Did you know that According to the U.S. Bureau of Labor and Statistics, developers will see job growth of 27% by 2024?
The problem is that everyone you know (your friends, family, professors, co-workers, etc) are LYING to you and most don’t even know it.
They tell you to…
Graduate from a "prestigious" university with an overpriced degree (which holds less weight than ever before)…
It’s too difficult to code
It’s too late to learn
You are not meant to code
This sounds pretty depressing, doesn’t it?
Yet, most people would succumb to other people’s opinions and would live a low quality life.
If you want more out of life, there is a better way.
Let me introduce you to The Amazing Escape Plan.
In this comprehensive, 3-in-1 course, you are going to Learn Java from scratch, understand core fundamentals of programming, solving Easy, Medium and Hard Level LeetCode Problems. You'll learn everything that you need to know to Crack Coding Interview rounds in your dream company starting How it works, the architecture, code execution, every single step in detail. We also cover the installation of tools that are required to write code in Java. We run our first Java program from scratch, providing a hands on demo of every step. We cover input and output in Java, data types, type conversion and casting, debugging, control flow, loops, and also solve a few problems.
Arrays and ArrayLists - We dive deep into how it works, the memory management, input/output, multidimensional arrays, dynamic arrays, working with functions, and solve some questions.
Strings and String Builder - We look into how it works internally, various operations, memory management, and some examples.
Searching Algorithms - We cover Linear Search & Binary Search in-depth. We cover the working, complexity analysis, code, and solve some LeetCode and FAANGM questions to strengthen the concepts.
Sorting Algorithms - In the sorting algorithm series, we cover Bubble sort, Selection sort, Insertion sort, Cycle Sort, Merge Sort in depth. We look at how the algorithm works, the complexity analysis, optimization, and code.
Pattern Questions - We'll look at how you can solve any coding patterns question in a step by step manner, and what the thought process should be like.
Time & Space Complexity - We'll go from beginner to advanced with “Time and Space Complexity Analysis”. We'll cover in-depth explanations of Big-O, Big-Omega, Theta and other notations
Recursion & Backtracking - Covers an introduction to Backtracking, along with maze path problems. An important video for interviews covering complete theory + code + tips.
Object Oriented Programming - In this section you'll master OOP Concepts like never before. This Module contains 7 lectures crossing over 5 hrs.
Linked Lists - One of the most important data structures for coding interviews. Here we also build the Linked List from scratch and see how it works internally. This module is also full of interview questions from Google, Facebook, Amazon, Microsoft, Apple, Twitter and LinkedIn ranging from LeetCode Easy to Hard.
Stacks and Queues - One of the most important data structures for coding interviews. Here we also build the data structures from scratch and see how it works internally. Along with the dynamic implementations, circular queues, exception handling and more.
Trees - One of the most important data structures for coding interviews. Here we also build the data structures from scratch and see how it works internally. Along with the Binary Trees, Binary Search Trees and Solving LeetCode Problems.
You have nothing to lose and so much to gain.
Register for this course and see more details by visiting:
OpenCourser.com/course/jhqjvx/data
What's inside
Learning objectives
- Learn various popular data structures and their algorithms.
- Develop your analytical skills on data structure and use then efficiently.
- Ace coding interviews given by some of the top tech companies
- Become a better developer by mastering computer science fundamentals
- Time and space complexity of algorithms, detailed discussion of logic to solve leetcode questions
- Code implementation in java
- Real coding interview questions from google, meta, amazon, adobe, microsoft etc.
- Learn java from scratch
- Learn various popular data structures and their algorithms.
- Develop your analytical skills on data structure and use then efficiently.
- Ace coding interviews given by some of the top tech companies
- Become a better developer by mastering computer science fundamentals
- Time and space complexity of algorithms, detailed discussion of logic to solve leetcode questions
- Code implementation in java
- Real coding interview questions from google, meta, amazon, adobe, microsoft etc.
- Learn java from scratch
Syllabus
Introduction
Introduction to Programming languages
Flow of Program - Flowcharts & Pseudocode
Introduction to Java - Installation & Architecture
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Syllabus
Introduction
Introduction to Programming languages
Flow of Program - Flowcharts & Pseudocode
Introduction to Java - Installation & Architecture
Read more
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Data Structures Algorithms in Java – SECRETS to Ace LeetCode.
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Career center
Learners who complete Data Structures Algorithms in Java – SECRETS to Ace LeetCode will develop knowledge and skills
that may be useful to these careers:
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications and systems. This role demands a deep understanding of efficient code, algorithmic problem-solving, and robust system architecture. The Data Structures Algorithms in Java course is a direct pathway to excel as a Software Engineer, providing comprehensive training in Java programming from scratch, alongside mastering core data structures like arrays, linked lists, stacks, queues, and trees. You will learn to implement and analyze sorting and searching algorithms, understand time and space complexity, and apply object oriented programming principles, preparing you thoroughly for the challenges of real-world software development and critical coding interviews at top tech companies. This course hones the analytical skills essential for crafting optimized and scalable software solutions.
Algorithms Engineer
Algorithms Engineer
An Algorithms Engineer specializes in designing, analyzing, and implementing complex computational algorithms to solve intricate problems across various domains, from scientific computing to data processing and artificial intelligence. This demanding role requires a profound theoretical and practical understanding of algorithmic efficiency and mathematical foundations. The Data Structures Algorithms in Java course is precisely tailored for aspiring Algorithms Engineers. You will delve deeply into various sorting and searching algorithms, understand advanced concepts like recursion and backtracking, and master the analysis of time and space complexity using Big-O, Big-Omega, and Theta notations. Building data structures like linked lists, trees, stacks, and queues from scratch provides invaluable insight into their internal workings, which is critical for innovating and optimizing algorithms in specialized engineering roles.
Research Scientist Computer Science
Research Scientist Computer Science
A Research Scientist in Computer Science typically conducts original research, develops new theories, algorithms, or systems, and publishes findings. This role often involves pushing the boundaries of current knowledge and requires a deep, theoretical, and practical understanding of computer science fundamentals. The Data Structures Algorithms in Java course provides an exceptionally strong foundation for an aspiring Research Scientist Computer Science. You will delve into advanced topics like recursion, backtracking, and comprehensive complexity analysis (Big-O, Big-Omega, Theta), which are critical for analyzing the efficiency of novel algorithms. Building data structures from scratch and solving complex LeetCode problems cultivates the analytical and problem-solving skills necessary for innovative research. This role frequently requires an advanced degree, such as a Master's or PhD, but the course furnishes you with vital practical and theoretical skills for such an academic and industry path.
Technical Lead
Technical Lead
A Technical Lead guides a team of developers, overseeing the technical design, architecture, and implementation of software projects. This leadership role demands not only excellent programming skills but also a deep understanding of computer science fundamentals to make informed architectural decisions and mentor team members effectively. The Data Structures Algorithms in Java course provides an invaluable foundation for an aspiring Technical Lead. Mastering Java programming, advanced data structures like linked lists, trees, stacks, and queues, and efficient algorithms is crucial for designing scalable and performant systems. The course's detailed discussion of time and space complexity analysis equips you to evaluate design choices critically, while the experience with real coding interview questions from top companies fosters the problem-solving acumen required to lead complex technical initiatives and inspire engineering excellence.
Backend Developer
Backend Developer
A Backend Developer builds and maintains the server-side logic, databases, and APIs that power web applications. This professional crafts the unseen infrastructure, ensuring data is processed, stored, and delivered efficiently and securely. The Data Structures Algorithms in Java course is exceptionally well-suited for a Backend Developer, as it focuses on core Java programming, a widely used language for backend systems, and provides an in-depth understanding of data structures and algorithms. Mastering concepts like linked lists, stacks, queues, and trees, along with time and space complexity analysis, directly translates to designing highly performant and scalable backend services. The practical experience with LeetCode problems also sharpens the analytical abilities needed to optimize server-side operations and handle complex data scenarios.
Systems Architect
Systems Architect
A Systems Architect is responsible for the overall design and blueprint of a software system, ensuring it meets functional and non-functional requirements such as scalability, performance, and security. This role requires a holistic view of technology and a deep understanding of software engineering principles. The Data Structures Algorithms in Java course provides core competencies that are highly beneficial for a Systems Architect. Your mastery of data structures and algorithms, coupled with a thorough understanding of time and space complexity, is essential for designing efficient and robust system components. The course's exploration of Object Oriented Programming, recursion, and backtracking, alongside building data structures from scratch, cultivates a strong foundational knowledge of how software operates at a fundamental level, empowering you to make sound architectural decisions that lead to resilient and high-performing systems. This role typically requires extensive experience, but the course provides a strong technical base.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains the infrastructure for data collection, storage, processing, and analysis. This role is crucial for ensuring that data is accessible and reliable for business intelligence and machine learning initiatives. The Data Structures Algorithms in Java course provides an excellent foundation for a Data Engineer, as robust programming skills in Java, coupled with a solid grasp of data structures and algorithms, are paramount for building efficient data pipelines and managing large datasets. Concepts such as arrays, linked lists, and trees are fundamental for organizing and manipulating data effectively, while understanding time and space complexity is vital for optimizing data processing jobs. The analytical approach to solving LeetCode problems also trains you to tackle complex data challenges with innovative and scalable solutions.
Full-Stack Developer
Full-Stack Developer
A Full Stack Developer works on both the front end and back end of web applications, requiring a versatile skill set that spans user interfaces, server-side logic, and database interactions. This professional needs a comprehensive understanding of how all parts of a software system integrate and perform. The Data Structures Algorithms in Java course offers substantial benefits for an aspiring Full Stack Developer, particularly reinforcing the backend capabilities. Mastery of Java programming, comprehensive data structures like arrays, linked lists, and trees, and efficient algorithms is critical for building robust and scalable server-side components. Furthermore, a deep understanding of time and space complexity helps in optimizing application performance across the entire stack. This course helps you build the foundational computer science knowledge that underpins efficient development on any part of the stack.
Quantitative Developer
Quantitative Developer
A Quantitative Developer, often found in financial institutions, develops and implements complex mathematical models and algorithms for pricing financial instruments, risk management, or high-frequency trading. This role demands exceptional programming skills, deep analytical abilities, and a strong understanding of computational efficiency due to the performance-critical nature of financial applications. The Data Structures Algorithms in Java course is a highly relevant foundation for a Quantitative Developer. Mastering Java from scratch, along with comprehensive data structures and algorithms, is crucial for coding intricate financial models and ensuring their optimal performance. The in-depth coverage of time and space complexity analysis directly applies to optimizing critical calculations, while tackling LeetCode-style problems cultivates the precise problem-solving mindset necessary for this exacting field. This role often requires an advanced degree in a quantitative field, but the course provides the essential computing groundwork.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, builds, and deploys machine learning models and systems. This role often involves implementing complex algorithms, optimizing model performance, and working with large datasets, requiring strong programming skills and an understanding of computational efficiency. The Data Structures Algorithms in Java course can be very helpful for a Machine Learning Engineer. While specific machine learning algorithms are not covered, the course provides a robust foundation in Java programming, data structures, and algorithms, which are critical for implementing and optimizing ML models efficiently. Understanding time and space complexity is essential for managing computational resources in machine learning tasks, and the problem-solving skills honed through LeetCode challenges prepare you to tackle the intricate logistical and algorithmic aspects of machine learning development. This course may be particularly useful for those seeking to implement custom algorithms or optimize existing frameworks.
Software Development Engineer in Test
Software Development Engineer in Test
A Software Development Engineer in Test, or SDET, plays a hybrid role, combining software development skills with quality assurance to design, develop, and maintain automated testing frameworks and tools. This requires a strong programming background to build robust, scalable, and efficient test solutions. The Data Structures Algorithms in Java course is highly relevant for an SDET. Your ability to code in Java from scratch, understand core programming fundamentals, and master data structures and algorithms directly translates into developing sophisticated test automation scripts and frameworks. The course's emphasis on time and space complexity helps in writing performant tests, while skills in debugging and problem-solving, honed through LeetCode challenges, are essential for identifying and resolving software defects effectively. This foundation helps you build test solutions that are as well-engineered as the product itself.
Embedded Software Engineer
Embedded Software Engineer
An Embedded Software Engineer develops software for microcontrollers and other embedded systems, which are specialized computer systems designed for specific functions within larger devices. This role often involves working with limited hardware resources, making efficient code and precise memory management critical. The Data Structures Algorithms in Java course may be helpful for an Embedded Software Engineer. While C or C++ are more common in very low-level embedded programming, the fundamental principles taught in this course, such as memory management (discussed with arrays and strings), data structures, and algorithms, are universally applicable. Understanding time and space complexity is vital for optimizing code for resource-constrained environments. The course's deep dive into core programming concepts and building structures from scratch helps you develop the disciplined approach to coding efficiency essential for embedded systems, regardless of the primary language used.
Frontend Developer
Frontend Developer
A Frontend Developer builds the user-facing part of websites and web applications, focusing on user experience, visual design, and client-side logic. While often associated with JavaScript, HTML, and CSS, a solid understanding of fundamental computer science principles can significantly enhance a Frontend Developer's capabilities. The Data Structures Algorithms in Java course may be useful for a Frontend Developer primarily by enhancing problem-solving and logical thinking skills. Although Java is not typically used for frontend development directly, the mastery of data structures like arrays and linked lists, and the ability to analyze algorithm efficiency through time and space complexity, translates into writing more optimized and performant client-side code, especially when dealing with complex data manipulation or UI rendering. The course fosters a disciplined approach to coding that improves overall development quality, irrespective of the specific programming language or framework.
Game Developer
Game Developer
A Game Developer designs and programs video games across various platforms, often specializing in engine programming, gameplay mechanics, or graphics. This field demands creative problem-solving and highly optimized code to ensure smooth and immersive user experiences. The Data Structures Algorithms in Java course may be useful for a Game Developer, particularly for those working on game logic, AI, or specific game systems where performance is paramount. Java is a language used in some game development contexts, such as Android games. A deep understanding of data structures like arrays, trees, and graphs (related to linked lists), along with efficient algorithms and time and space complexity analysis, is crucial for optimizing game performance, managing game states, and creating responsive and engaging gameplay experiences, especially for complex systems. The course helps build the foundational skills to approach performance-critical programming.
DevOps Engineer
DevOps Engineer
A DevOps Engineer bridges the gap between development and operations, focusing on automating and streamlining the software development lifecycle, from code commit to deployment and monitoring. This role requires a blend of coding skills, system administration knowledge, and an understanding of scalable infrastructure. The Data Structures Algorithms in Java course may be useful for a DevOps Engineer. While direct application of complex algorithms might be less frequent than for a core software developer, strong foundational programming skills in Java can be very beneficial for writing custom automation scripts, developing internal tools, or working with Java-based build and deployment systems. Understanding efficient coding practices and system architecture, which is reinforced by the course's focus on core fundamentals and code execution, helps in building robust and performant automation pipelines and managing complex software deployments effectively.
For more career information including salaries, visit:
OpenCourser.com/course/jhqjvx/data
Reading list
We've selected 23 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Structures Algorithms in Java – SECRETS to Ace LeetCode.
Is the gold standard for preparing for technical interviews at top tech companies like Google and Amazon, aligning perfectly with the course's 'Ace LeetCode' goal. It provides detailed walkthroughs of data structure fundamentals and algorithm strategies that mirror the course syllabus. It is especially valuable as a bridge between theoretical knowledge and the practical problem-solving required for high-stakes coding rounds.
Direct supplement to the LeetCode focus of the course, offering a massive collection of problems categorized by data structure. It provides high-quality Java solutions that emphasize clean code and efficiency, which is crucial for the FAANG-level preparation mentioned in the course objectives. It is best used as a workbook alongside the course videos to practice implementation.
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As a widely used textbook in academic institutions, this book provides the most authoritative Java-based implementations of the algorithms covered in the course. It is an essential reference for understanding the internal mechanics of sorting and searching within the Java ecosystem. The authors' focus on performance and memory management adds significant depth to the course's discussion on time and space complexity.
Is specifically designed for interview preparation, making it a perfect companion to the course's 'SECRETS to Ace LeetCode.' It offers multiple solutions to each problem with varying time and space complexities, which helps students understand optimization. It serves as a useful reference tool for quick review before a technical interview.
Staple in university computer science programs, providing a seamless transition from basic Java syntax to advanced data structures. It includes numerous exercises that are very similar to the LeetCode problems discussed in the course. Its comprehensive nature makes it an ideal replacement for the course for students who prefer a structured, text-heavy learning path.
This comprehensive academic textbook that follows a design pattern approach, making it a great reference for the Object-Oriented Programming (OOP) section of the course. It covers the Java Collections Framework in detail, which key part of the course syllabus. It adds breadth by discussing more advanced structures like heaps and graphs that the course touches upon.
Is highly recommended for beginners who find traditional textbooks too dense, matching the course's accessible 'Amazing Escape Plan' tone. It uses a visual and intuitive approach to explain recursion, dynamic programming, and Big O notation without heavy math. It serves as excellent prerequisite reading for students who are new to programming fundamentals.
Is known for its rigorous approach to algorithm analysis, making it an excellent resource for mastering the 'Time and Space Complexity' section of the course. It covers advanced topics like balanced search trees and hashing in great detail. It is highly reputable within the field and used by many top-tier universities as a primary textbook.
Is excellent for understanding the abstraction of data structures, helping students think about the data before the implementation. It aligns well with the course modules on Stacks, Queues, and Trees by providing a very clear pedagogical structure. It is commonly used as a textbook for second-semester computer science students.
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The third edition of this classic provides a modern, beginner-friendly introduction to Java SE 17, which aligns with the course's 'Java from scratch' modules. Its interactive format is ideal for learners who struggle with traditional technical documentation. It provides the necessary prerequisite knowledge of JVM architecture and memory management mentioned in the course description.
Focuses on the communication and thought process of the interview, complementing the course's technical content. It provides strategies for solving problems on a whiteboard or during a live coding session, which is essential for 'cracking' the interview. It valuable additional reading for the 'soft skills' side of the technical hiring process.
Commonly known as CLRS, this recently updated fourth edition is the definitive theoretical reference for algorithm design and analysis. While the course provides a practical 'how-to,' this book offers the rigorous mathematical background and proofs for Big O notation and complex data structures. It is more valuable as a comprehensive reference tool for students who want to master the 'why' behind the logic.
Is highly regarded for its 'War Stories' which describe how algorithms are used to solve real-world industry problems. It is particularly useful for the course's goal of developing analytical skills, as it focuses on the logic of choosing the right data structure for a given problem. The recently published third edition includes updated content on modern algorithmic challenges.
Provides a deep dive into the Java language itself, including the architecture and code execution mentioned in the course introduction. It is an authoritative reference for professional developers and covers the Java Collections Framework with exceptional clarity. Use this to supplement the course's 'Java from scratch' section for a more professional-level understanding.
Perfect for visual learners, this book simplifies complex topics like recursion and sorting through illustrations and clear analogies. It provides an excellent high-level overview that can help students grasp the 'big picture' before diving into the course's technical Java implementations. It fantastic introductory tool for those intimidated by the technical jargon of computer science.
This practical reference tool that focuses on the most important algorithms for daily programming tasks. It provides clear Java implementations and performance analysis without the academic fluff. It is particularly useful for the course's 'Time and Space Complexity' module, offering quick-lookup tables for various algorithmic costs.
Written by one of the world's leading programming authors, this book is an excellent reference for the Java syntax and core fundamentals taught in the first half of the course. It covers everything from basic loops to the latest Java features, providing a solid foundation for the more complex DSA topics that follow. It is commonly used as a textbook for introductory programming courses.
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Contains over 300 practical problems that help solidify the Java knowledge gained in the course. It covers modern Java features and common pitfalls that are often tested in technical interviews but might be missed in a standard DSA course. It great resource for hands-on practice once the course fundamentals are mastered.
Save
While not a DSA book specifically, this is the essential guide to writing high-quality Java code, which is vital for the professional development aspect of the course. It teaches best practices for classes, interfaces, and generics that will make the student's LeetCode solutions more professional. Reading this ensures that the 'Java from scratch' learning objective leads to industry-standard coding habits.
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Provides a broad overview of the Java ecosystem, including tools and libraries that go beyond the basics. It is helpful for the course's goal of becoming a 'better developer' by showing how Java is used in real-world applications. It serves as a great reference for the installation and architecture topics discussed in the introductory modules.
Focuses on the practical application of data structures, particularly how they are used in web search and information retrieval. It emphasizes the use of Java interfaces, which adds depth to the course's OOP and Collections Framework modules. It concise and useful reference for understanding how to use existing libraries rather than just building them from scratch.
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While the course focuses on solving LeetCode problems, this book ensures that the solutions are readable and maintainable. Most FAANG interviewers look for 'clean code' as much as they look for the correct algorithm. vital professional development resource that will set the student apart from other candidates who only focus on logic.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jhqjvx/data
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