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Pratik Singhal

Picture this: You're sitting in the hot seat of a coding interview, faced with a challenging DSA problem. How do you tackle it with confidence and perfection? That's where my course comes in.

In this course, I am taking you straight to the heart of the action – the top 130 Leetcode problems. Why these specific ones? Because they're the ones tech companies love to throw your way. By mastering these, you'll be ready to ace any coding interview that comes your way.

If you’re wondering why Leetcode?

Read more

Picture this: You're sitting in the hot seat of a coding interview, faced with a challenging DSA problem. How do you tackle it with confidence and perfection? That's where my course comes in.

In this course, I am taking you straight to the heart of the action – the top 130 Leetcode problems. Why these specific ones? Because they're the ones tech companies love to throw your way. By mastering these, you'll be ready to ace any coding interview that comes your way.

If you’re wondering why Leetcode?

Leetcode is the most popular platform that offers a vast array of coding challenges, frequently used by tech companies in their hiring processes.

Here's why this course is will help you:

We're not simply tossing problems your way and crossing our fingers. Nope, not here.

  • We will together dive deep into each problem for invaluable insights into underlying concepts and problem-solving techniques, helping you to truly understand and conquer every challenge.

  • You’ll learn systematic approaches to problem-solving. We’ll help you break them into manageable tasks and craft efficient algorithms, so you can confidently tackle any challenge that comes your way.

  • One standout feature of this course is the live code implementation. You'll see each problem solved in real-time, giving you a firsthand look at the coding process.

  • Enhance your coding abilities through practical, hands-on learning, ensuring you're well-prepared for real-world scenarios.

  • Discover efficient coding practices, optimization techniques, and common pitfalls to avoid, equipping you with the skills to write clean, efficient code.

  • Follow along step-by-step as we dissect each problem in detail, guiding you through the thought process and live code implementation.

  • You get to access code sample files accompanying the video lectures, serving as valuable references and guides to support your learning journey and help you implement solutions effectively.

Enroll now

What's inside

Learning objectives

  • Top 130 coding interview problems on leetcode
  • Data structure & algorithms theory with implementation
  • Leetcode practice problems on dynamic programming, greedy algorithms in java
  • Leetcode practice problems on graphs, trees, backtracking in java
  • Leetcode practice problems on arrays, sliding window, two pointer, ad hoc problems in java

Syllabus

Course Introduction
How to get started with Leetcode ?
In this section we will learn how to calculate time and space complexity for any algorithm from scratch. By the end of this section you will become proficient in time and space complexity calculation
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Develops expertise of top 130 Leetcode problems, essential for passing coding interview challenges
Strengthens foundational coding skills and deepens understanding of data structures and algorithms
Covers a variety of problem-solving techniques, including dynamic programming, greedy algorithms, and backtracking
Provides hands-on practice and prepares learners to tackle real-world coding challenges
Led by Pratik Singhal, an expert in coding interviews with a proven track record

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Reviews summary

Comprehensive leetcode prep in java

According to learners, this course is designed as a highly practical and comprehensive guide for coding interview preparation, specifically targeting Data Structures and Algorithms in Java. Students appreciate its focus on mastering 130 top Leetcode problems, which are presented with live code implementation and a systematic approach to problem-solving. The course's emphasis on efficient coding practices and detailed explanations of underlying concepts makes it a valuable resource for those seeking to ace technical interviews.
Solutions and implementations are exclusively in Java.
"As a Java developer, I found the Java-specific implementations very beneficial for my learning."
"It's great for Java users, but those looking for other languages will need to adapt the concepts."
"All the code examples are provided in Java, which is perfect for my current programming focus."
Explains core Data Structures & Algorithms concepts.
"The initial sections on time and space complexity were very helpful in building foundational knowledge."
"I gained a deeper understanding of underlying DSA concepts before diving into the specific problems."
"It really clarified how to approach complex algorithms systematically from a theoretical standpoint."
Features hands-on live coding sessions for problem-solving.
"The live code implementation is a key strength, allowing me to follow the instructor's thought process clearly."
"I appreciate seeing problems solved in real-time, which significantly clarifies the coding process."
"The hands-on approach with accompanying code samples makes learning very effective and practical."
A wide array of high-frequency Leetcode problems are covered.
"This course delivers on its promise to tackle 130 top Leetcode problems across various DSA topics, which is highly beneficial."
"I found the range of problems covered, from arrays to graphs, excellent for interview preparation."
"It's a solid resource for anyone looking to master typical coding interview questions effectively."
Tailored specifically for acing technical coding interviews.
"The course's direct focus on tech company interview problems makes it highly relevant for job seekers."
"I feel much more prepared for coding interviews after going through these systematic approaches."
"This is exactly what I needed to boost my confidence for challenging DSA questions in an interview setting."
Pace might be challenging for absolute beginners in DSA.
"While comprehensive, I found that beginners to DSA might find the sheer volume of problems intense."
"I needed some prior DSA exposure to fully keep up with the rapid pace of problem-solving."
"It's probably best for those with some basic programming and algorithm understanding already."

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 Data Structures & Algorithms in Java + 130 Leetcode Problems with these activities:
Review Basic Programming Concepts
Review basic programming concepts to refresh your knowledge and ensure you have a solid foundation for the course.
Browse courses on Programming Fundamentals
Show steps
  • Go over your notes or textbooks from previous programming courses.
  • Practice writing simple code snippets to implement basic programming concepts such as variables, data types, and control flow.
  • Solve easy LeetCode problems to apply your refreshed programming skills.
Organize Your Course Materials
Organize your course materials such as notes, assignments, quizzes, and exams to improve your ability to find and review them later.
Show steps
  • Create folders or use a digital tool to organize your course materials.
  • Label and group related materials together.
  • Regularly update and review your organized materials.
Read a Book on Data Structures and Algorithms
Review a book on data structures and algorithms to strengthen your foundational knowledge and prepare for coding interviews.
Show steps
  • Choose a book on data structures and algorithms that aligns with your skill level.
  • Read the book thoroughly and take notes on important concepts.
  • Practice implementing data structures and algorithms in the programming language of your choice.
  • Solve LeetCode problems using the concepts you learned from the book.
  • Discuss the book and your learnings with peers or instructors.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Study Group for LeetCode Problems
Join a study group to collaborate with other students, discuss different approaches to LeetCode problems, and learn from each other.
Show steps
  • Find a study group or create your own with classmates.
  • Choose LeetCode problems to work on together.
  • Meet regularly to discuss your solutions and learn from each other.
  • Share resources and tips related to LeetCode problems.
  • Provide peer support and encouragement to each other.
Watch Video Lectures on LeetCode Problems
Watch video lectures from the course to gain insights into different LeetCode problems and solution approaches.
Show steps
  • Choose a LeetCode problem from the course syllabus.
  • Watch the corresponding video lecture for that problem.
  • Take notes on the problem-solving approach and implementation details.
  • Pause the video and try to solve the problem on your own.
  • Resume the video to check your solution and learn from the instructor's approach. (recommended)
Practice LeetCode Problems
Practice solving LeetCode problems to improve your problem-solving skills and prepare for coding interviews.
Show steps
  • Pick a LeetCode problem from the course syllabus.
  • Read the problem statement carefully and understand the requirements.
  • Break down the problem into smaller subproblems.
  • Implement your solution in the programming language of your choice. (e.g. Java)
  • Test your solution against the given test cases.
Create a LeetCode Problem Collection
Create a collection of LeetCode problems that you have solved or found particularly challenging to reinforce your learning and prepare for coding interviews.
Show steps
  • Identify LeetCode problems that you found interesting or challenging.
  • Organize the problems into categories or topics.
  • Create a document or use a tool to store the problem statements, your solutions, and any additional notes.
  • Review your collection regularly to refresh your knowledge and identify areas for improvement.
Write a Summary of a LeetCode Problem
Summarize a LeetCode problem to solidify your understanding and improve your communication skills.
Show steps
  • Pick a LeetCode problem from the course syllabus.
  • Solve the problem on your own or with the help of course materials.
  • Write a summary that includes the problem statement, your solution approach, and the time and space complexity of your solution.
  • Proofread your summary for clarity and accuracy.
  • Share your summary with a peer or instructor for feedback.

Career center

Learners who complete Data Structures & Algorithms in Java + 130 Leetcode Problems will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 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 + 130 Leetcode Problems.
This foundational and comprehensive text covering a wide range of algorithms, including a dedicated chapter on greedy algorithms. It provides a rigorous analysis of algorithm correctness and efficiency. is commonly used as a textbook in undergraduate and graduate computer science programs and serves as an essential reference for professionals.
Provides a comprehensive overview of common coding interview questions and solutions, covering topics such as data structures, algorithms, and problem-solving strategies. It is highly relevant to LeetCode, as it can help candidates prepare for and excel in coding interviews.
Considered a must-read for any serious Java programmer, this book provides invaluable advice on writing robust, efficient, and well-designed code. It delves into best practices, common pitfalls, and advanced topics. It is highly recommended for intermediate to advanced programmers and professionals looking to deepen their understanding and improve their coding style.
While not exclusively a Java book, 'Clean Code' is highly recommended for Java developers. It focuses on the principles and practices of writing readable, maintainable, and testable code. is crucial for anyone looking to improve their software craftsmanship, regardless of experience level. It complements technical Java knowledge with essential coding standards.
This comprehensive textbook provides a broad overview of graph theory, covering fundamental concepts, algorithms, and applications. It is suitable for undergraduate and graduate students, as well as researchers in computer science, mathematics, and engineering.
Often referred to as "CLRS," this book comprehensive and widely-used textbook for undergraduate and graduate-level algorithms courses. It provides in-depth knowledge of data structures and algorithms, including their analysis and implementation. While it assumes some mathematical familiarity, it's an encyclopedic reference valuable for both learning and as a long-term resource.
Is the definitive guide to writing correct and efficient multithreaded Java applications. Concurrency complex topic, and this book provides the necessary knowledge and patterns to handle it effectively. It's essential reading for graduate students and working professionals dealing with concurrent programming.
This seminal work provides a catalog of refactorings to improve the design of existing code. It explains how to identify code smells and apply techniques to make code more understandable and maintainable. is essential for developers who work with existing Java codebases and want to improve their design.
Offers a comprehensive treatment of data structures and algorithms, suitable for academic settings. It covers various data types and algorithms for sorting, searching, and processing. The book is known for its detailed explanations and includes an online portal with source code, making it a strong resource for solidifying understanding.
Comprehensive treatment of algorithmics, from the foundations to advanced topics such as randomized algorithms and approximation algorithms. It is written in a clear and concise style, and it includes many examples and exercises.
This Japanese translation of the renowned textbook 'Introduction to Algorithms' provides a comprehensive overview of arrays, including their analysis, implementation, and applications in algorithm design. It is an excellent resource for readers seeking a thorough understanding of the topic.
Provides an introduction to the field of reinforcement learning, which subfield of machine learning that deals with sequential decision-making. Reinforcement learning is closely related to dynamic programming and this book provides a good overview of the field and its applications.
This classic book by Donald Knuth provides a comprehensive treatment of dynamic programming. While not specifically focused on LeetCode problems, it valuable resource for understanding the fundamental concepts and techniques of dynamic programming, which common technique used in solving LeetCode problems.
Provides a comprehensive overview of extremal graph theory, covering fundamental concepts, models, and applications in various fields. It is suitable for researchers and students in computer science, mathematics, and other disciplines.
Provides a comprehensive overview of network science, covering fundamental concepts, models, and applications in various fields. It is suitable for researchers and students in computer science, physics, biology, and other disciplines.
This German-language textbook provides a comprehensive overview of graph theory, covering both fundamental concepts and advanced topics. It is suitable for undergraduate and graduate students in mathematics and computer science.
This advanced textbook covers combinatorial optimization problems related to graphs and matroids, such as network flow problems and matching problems. It is suitable for graduate students and researchers in computer science, operations research, and mathematics.
Offers a practical approach to algorithm design, complementing theoretical texts with real-world examples and a catalog of algorithmic problems. It includes coverage of greedy algorithms and is valuable for understanding how to apply these techniques to solve problems. It useful reference tool and supplementary reading for students and professionals.
For those interested in enterprise Java development, this book is an essential guide to the Spring framework. Spring is widely used for building Java applications, and this book covers its core features and best practices. It is valuable for undergraduate students and professionals focusing on enterprise Java.
This textbook is suitable for advanced data structures or introductory graduate-level algorithm analysis courses. It bridges the gap between foundational data structures and more advanced analysis techniques. The book provides a rigorous and in-depth analysis of algorithms and their implementation in C++.
While not a Java-specific book, this is highly relevant for Java developers building large-scale, distributed systems. It covers fundamental concepts in data systems, which are crucial for designing robust Java applications in a professional setting.
Introduces fundamental design patterns in a highly engaging and easy-to-understand manner. While not solely focused on Java, it uses Java examples extensively. Understanding design patterns is vital for writing well-structured and maintainable Java applications, making this book valuable for students and professionals.
A respected textbook that focuses on the design of algorithms, presenting various techniques including greedy algorithms through a problem-driven approach. It is suitable for undergraduate and graduate students and provides insights into the creative process of algorithm design.
Is highly relevant for professionals working with or interested in microservices architecture using Java. It provides a holistic view of designing, building, and deploying microservices. While not strictly a Java language book, it addresses a key architectural style in modern Java development.
Another essential text on approximation algorithms, covering various design techniques, including those based on greedy approaches. It is geared towards graduate students and researchers and provides a comprehensive overview of the field.
Is known for its comprehensive coverage and clear explanations of Java concepts, emphasizing the 'why' behind the language features. It's a strong resource for intermediate and advanced learners seeking a deeper understanding of Java and object-oriented programming.
A comprehensive introduction to Java programming, this book covers the basics thoroughly, from writing and compiling code to understanding keywords and syntax. It's suitable for beginners and can serve as a good reference for fundamental concepts. The latest editions are updated to cover newer Java versions.
Provides a solid theoretical and practical foundation in data structures and algorithms using Java. It's a standard textbook in many university computer science programs and is crucial for understanding the efficiency and design of programs. Essential for undergraduate and graduate students.
For Java developers working with containerized applications and cloud deployments, understanding Kubernetes is essential. provides a comprehensive guide to deploying and managing applications on Kubernetes. It's highly relevant for professionals in a DevOps environment.
Another foundational book for software developers, this provides timeless advice on a wide range of topics, including development methodologies, personal responsibility, and career development. While not Java-specific, its principles are highly relevant and beneficial for any Java programmer seeking to improve their overall development skills.
Key resource for understanding approximation algorithms, a field where greedy strategies are frequently used to find near-optimal solutions for NP-hard problems. It is suitable for graduate students and researchers interested in the theoretical aspects of algorithms for difficult problems.
A widely used textbook that covers essential algorithms and data structures, with implementations in Java. While not solely focused on greedy algorithms, it provides a solid foundation in algorithmic thinking and covers greedy approaches within broader topics like graph algorithms. It is suitable for undergraduate study and as a reference.
This introductory textbook provides a clear and concise introduction to graph theory, focusing on fundamental concepts and applications in computer science and other fields. It is suitable for undergraduate students with no prior knowledge of graph theory.
Provides a comprehensive overview of random graphs, covering fundamental concepts, models, and applications in various fields. It is suitable for researchers and students in computer science, mathematics, and other disciplines.
Explores the use of arrays in modern programming languages and environments, discussing advanced topics such as concurrent programming, memory management, and performance optimization. It is particularly relevant for readers interested in understanding how arrays are used in real-world software systems.
Another excellent resource for competitive programmers, this book covers essential algorithms and techniques used in programming contests, including backtracking. It provides theoretical explanations and numerous practice problems with solutions, making it ideal for students and professionals looking to excel in algorithmic problem-solving.
Introduces the principles of Test-Driven Development (TDD) using simple examples. While the examples are not exclusively in Java, the concepts are directly applicable to Java development. TDD fundamental practice for writing robust and maintainable code, making this book valuable for all levels.
Is geared towards students participating in programming contests. It covers a wide range of algorithmic techniques, including backtracking, and provides numerous problems for practice. It's a valuable resource for advanced undergraduate and graduate students looking to hone their algorithmic skills and apply backtracking in competitive settings.
Provides a comprehensive overview of graph theory and its applications in various fields. It is suitable for undergraduate and graduate students in computer science and mathematics.
This textbook offers a rigorous introduction to data structures and algorithms with implementations in C++. It covers a wide range of topics and is suitable for undergraduate computer science programs.
Offers a very approachable and illustrated guide to algorithms, making it excellent for beginners. It uses diagrams and clear explanations to introduce fundamental concepts like sorting and searching. It's a great starting point before diving into more theoretically dense texts.
This text offers a concise and mathematically elegant introduction to algorithms, including core concepts related to greedy algorithms. It is often used in undergraduate courses and provides a good balance of theory and intuition. It is valuable for solidifying understanding through its clear explanations.
Explores the functional programming features introduced in Java 8, such as lambda expressions and streams. It helps developers write more concise and expressive code. This is particularly relevant for those looking to leverage modern Java language features.
Provides a comprehensive overview of data structures and algorithms, including their implementation in C++. It covers arrays as a fundamental data structure and discusses their use in various algorithms and applications.
Introduces data structures and algorithms using JavaScript. It covers fundamental concepts such as arrays, linked lists, and trees, as well as more advanced topics such as graphs and dynamic programming. While not specifically designed for LeetCode problems, it provides a good foundation for solving algorithmic challenges in JavaScript.

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