Leetcode for Beginners: 30 Leetcode Challenge from Udemy

This course is for beginners who are starting out and want to learn leetcode. If you are planning to crack FAANG/any prod-based company interview then the course is going to give you a good foundation to start. This contains the 30-must do leetcode problem. For each problem, we will discuss a step-by-step guide how to solve and evaluate time and space compleity and optimise them. This course helps to use proper data structure and will help you to write better code.The goal of the course is to solve "30 most FAQ interview questions" and to give you a framework to answer ANY leetcode interview questions that you can see in the real interview. We will teach you the patterns which will help you identify the right data structure for right problem so that any new question that you get, you have the pattern in mind which help you to solve the problem in your programming interview.

Data Structures Used:

* Arrays

* Matrices

* Hash Tables

* Linked lists

* Stacks

* Queues

* Tree

* Binary Search Trees

* Heap

* Priority Queues

* Graphs

* Adjacency List

* Adjacency Matrix

* DFS

* Dynamic Programming

Taught by:

Bijaya is an instructor who has over 12 years of experience and worked in multiple countries. He started training students while he was doing research work at IIT Delhi in the field of Algorithm. He published multiple research papers in the field of algorithms. He has already trained more than 1200 students. If you would like to know more stay in touch :)

What's inside

Learning objectives

The goal of the course is to solve "30 most faq's interview question" and to give you a framework to solve any leetcode interview problem.
Start preparing for faang company, lets start from here

30 must do leetcode problems for beginners
Leetcode problems for beginners

The goal of the course is to solve "30 most faq's interview question" and to give you a framework to solve any leetcode interview problem.
Start preparing for faang company, lets start from here
30 must do leetcode problems for beginners
Leetcode problems for beginners

Syllabus

Introduction

Reverse String - leetcode 344

Find All Numbers Disappeared in an Array - leetcode - 448

Part-2 - Find All Numbers Disappeared in an Array

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers data structures like arrays, matrices, hash tables, linked lists, stacks, queues, trees, and graphs, which are fundamental for coding interviews and software development

Focuses on solving 30 frequently asked LeetCode problems, providing a solid foundation for tackling coding interview questions at FAANG and other tech companies

Explores dynamic programming, a powerful technique used to solve optimization problems, which is a valuable skill for software engineers and algorithm designers

Taught by an instructor with over 12 years of experience and research background at IIT Delhi, which suggests a strong understanding of algorithms and data structures

Requires learners to engage with LeetCode, which may require creating an account and familiarizing oneself with the platform's interface and problem submission process

Reviews summary

Beginner's guide to leetcode interviews

According to learners, this course provides a solid foundation in essential data structures and algorithms, making it a good starting point for those new to Leetcode and interview preparation. Many found the explanations clear and easy to follow, particularly appreciating the instructor's step-by-step approach to solving problems. While it covers the 30 must-do problems as advertised and introduces key patterns, some students noted that the course serves as an introduction rather than a comprehensive deep dive, suggesting the need for further practice beyond the course content to truly master interview-level problems. Overall, it's seen as a helpful first step for beginners.

Focus on a curated list of 30 problems.

"Liked that he picked 30 important problems."

"The selection of problems was good for getting started."

"Focusing on 30 problems made it less overwhelming as a beginner."

Reviews appreciate coverage of basic data structures.

"The course covers essential data structures well."

"It helped me understand basic data structures needed for interviews."

"I got a solid understanding of fundamental algorithms and data structures."

"The review of arrays, hash tables, and linked lists was very helpful."

Focuses on logic and step-by-step solutions.

"I really liked the step-by-step approach to solving the problems."

"Bijaya goes through problems step-by-step, which is helpful."

"The way he breaks down the logic for each problem is excellent."

"I learned a good framework for thinking about how to approach Leetcode problems."

Ideal for beginners new to Leetcode/interviews.

"This course is a good starting point for beginners."

"It's great for beginners who are just starting out with Leetcode."

"This course is very helpful to start your Leetcode journey."

"As a beginner, I found this course very approachable and helpful to get started."

Instructor explains concepts and solutions well.

"The instructor is very clear and easy to understand."

"Bijaya explains the questions in a very easy to understand way."

"He goes over the problems very clearly and explains the logic step by step."

"The instructor's explanations were very clear and made complex topics accessible."

Course is intro, requires supplemental study.

"This is a good start, but definitely requires more practice afterwards."

"The course is just an introduction, you need to do more problems on your own."

"While helpful, it's not enough on its own to crack FAANG interviews."

"I felt it was a helpful overview, but I need to supplement with other resources."

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 Leetcode for Beginners: 30 Leetcode Challenge with these activities:

Review Data Structures and Algorithms Fundamentals

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Solidify your understanding of fundamental data structures and algorithms concepts before diving into LeetCode problems. This will make it easier to understand the solutions and apply them to new problems.

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Review basic data structures like arrays, linked lists, stacks, and queues.
Study fundamental algorithms like searching and sorting.
Practice implementing these data structures and algorithms in your preferred language.

Review Basic Data Structures

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Solidify your understanding of fundamental data structures before diving into LeetCode problems. This will make it easier to understand the solutions and apply them to new problems.

Browse courses on Arrays

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Read about the properties of each data structure.
Implement each data structure from scratch.
Solve simple problems using each data structure.

Practice Array Manipulation Problems

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Reinforce your understanding of array manipulation techniques by solving a variety of LeetCode problems focused on arrays. This will improve your problem-solving skills and familiarity with common array patterns.

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Solve array-related problems on LeetCode, focusing on different patterns.
Analyze the time and space complexity of your solutions.
Compare your solutions with others and identify areas for improvement.

Nine other activities

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Solve Easy LeetCode Problems

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Practice solving easy LeetCode problems to build confidence and familiarity with the platform. Focus on problems that utilize the data structures covered in the course.

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Filter LeetCode problems by difficulty and data structure.
Attempt to solve each problem independently.
Review the official solutions and other community solutions.
Refactor your code based on what you learned.

Participate in Peer LeetCode Study Group

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Collaborate with peers to solve LeetCode problems and discuss different approaches. This will expose you to new perspectives and help you learn from others' experiences.

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Form a study group with other students taking the course.
Choose LeetCode problems to solve together during the session.
Discuss different approaches and solutions with your peers.
Explain your reasoning and learn from others' explanations.

Participate in Peer Coding Sessions

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Collaborate with peers to solve LeetCode problems and discuss different approaches. This will help you learn from others and improve your problem-solving skills.

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Find a study partner or join a coding group.
Choose a set of LeetCode problems to work on together.
Discuss your solutions and provide feedback to each other.

Create a Video Explanation of a LeetCode Solution

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Deepen your understanding of a specific LeetCode problem by creating a video explanation of your solution. This will force you to articulate your thought process and identify any gaps in your knowledge.

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Choose a LeetCode problem that you found challenging or interesting.
Record a video explaining your solution step-by-step.
Explain the time and space complexity of your solution.
Share your video with others and solicit feedback.

Create a LeetCode Problem Tracker

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Build a tool to track your progress on LeetCode and identify areas where you need to improve. This will help you stay organized and motivated.

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Design the data structure for your tracker.
Implement the tracker using a programming language of your choice.
Add features to track your progress and identify weaknesses.
Use your tracker to guide your LeetCode practice.

Study Advanced Data Structures and Algorithms

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Explore more advanced data structures and algorithms to expand your knowledge and tackle more challenging LeetCode problems. This will prepare you for more complex interview questions.

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Identify areas where you want to improve.
Find tutorials and resources on advanced topics.
Practice solving LeetCode problems that utilize these concepts.

Build a LeetCode Problem Tracker

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Develop a personal project to track your progress on LeetCode problems. This will help you stay organized, identify areas for improvement, and build a portfolio of your work.

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Design a database or spreadsheet to store information about LeetCode problems.
Implement features to track your progress, such as problem status, difficulty, and solution code.
Add features to visualize your progress and identify areas where you need to focus.

Participate in LeetCode Contests

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Test your skills and compete against other LeetCode users in timed contests. This will help you improve your speed and accuracy.

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Register for upcoming LeetCode contests.
Practice solving problems under time pressure.
Analyze your performance and identify areas for improvement.

Mentor Beginner LeetCode Users

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Reinforce your understanding of LeetCode concepts by helping others. Explaining concepts to others will solidify your own knowledge.

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Find a beginner LeetCode user to mentor.
Help them understand the basics of data structures and algorithms.
Guide them through solving LeetCode problems.

Career center

Learners who complete Leetcode for Beginners: 30 Leetcode Challenge will develop knowledge and skills that may be useful to these careers:

Software Engineer

Software Engineers craft and maintain the applications that power our digital world. This role demands a strong understanding of data structures and algorithms. A course like this one helps build a foundation in essential data structures such as arrays, linked lists, trees, and graphs, along with related algorithms. These are core to solving many software engineering challenges. Mastering these concepts can help a software engineer write efficient and optimized code, which is crucial for performance. Especially valuable are the sections on dynamic programming and binary search, which offer tools to tackle more complex problems encountered in software development.

See salaries and explore the career path for Software Engineer

Algorithm Developer

Algorithm Developers design and implement algorithms for various applications and systems. The emphasis on data structures and problem-solving techniques in this course directly aligns with the skill set required for this role. The focus on time and space complexity analysis is especially relevant. The knowledge of data structures, such as hash tables, heaps, and graphs that this course provides, can help algorithm developers design efficient and effective solutions. The coverage of common interview questions is also beneficial, as it exposes learners to a wide range of algorithmic problems and solution strategies.

See salaries and explore the career path for Algorithm Developer

Back-End Developer

Back End Developers work on the server-side logic and databases that power applications. This role requires a strong grasp of data structures and algorithms. This course directly addresses this need by covering essential concepts such as linked lists, trees, graphs, and hash tables. A back end developer will see that learning how to optimize time and space complexity with this course translates to writing efficient and scalable code. The exposure to common interview questions is also valuable, since it prepares learners for the types of technical challenges they may face in back end development roles.

See salaries and explore the career path for Back-End Developer

Full-Stack Developer

Full Stack Developers work on both the front end and back end of web applications. As a hybrid role, full stack developers benefit from a broad understanding of data structures and algorithms. While the front end often involves user interface work, the back end demands efficient data management and algorithmic thinking. This course helps by building a foundation in essential data structures, such as arrays, linked lists, and trees. Such knowledge then contributes to a well-rounded full stack skillset. Coverage of dynamic programming and graph algorithms may be useful for tackling more complex challenges.

See salaries and explore the career path for Full-Stack Developer

Technical Lead

Technical Leads guide and mentor development teams, making architectural decisions and ensuring the quality of code. Although a technical lead spends less time writing code directly, a deep knowledge of data structures and algorithms is invaluable for guiding team members and making informed technical choices. This course may be useful in reinforcing such knowledge. A technical lead will make use of the understanding of time and space complexity to evaluate different design options and identify potential performance bottlenecks. The ability to solve algorithmic problems is also essential for mentoring junior developers and providing guidance on coding challenges.

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Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models. This course may be helpful for gaining a stronger grasp on the underlying data structures and algorithms that many machine learning algorithms rely on. This includes tree-based methods, graph algorithms, and dynamic programming techniques. While a Machine Learning Engineer requires expertise in machine learning frameworks, the ability to optimize code and understand the computational implications of different approaches is essential. The course helps a machine learning engineer write efficient code. The knowledge of data structures such as heaps and priority queues is also relevant in certain machine learning applications.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists analyze and interpret complex data sets. While this role involves statistical modeling, familiarity with data structures and algorithms is critical for data manipulation and optimization. This course may be useful in understanding how to manage and process data efficiently using arrays, matrices, and hash tables. A data scientist will also find that the material on tree-based structures and graph algorithms can be helpful for certain types of data analysis and modeling tasks. Understanding the time and space complexity of different algorithms, as taught in this course, can inform decisions about the most efficient ways to handle large datasets.

See salaries and explore the career path for Data Scientist

Data Engineer

Data Engineers build and maintain the infrastructure for data storage and processing. This course may be useful for understanding how data structures impact the efficiency of data pipelines. While data engineering focuses on tools and technologies like Spark and Hadoop, a solid grasp of basic algorithms and data structures helps to optimize data processing workflows. The course may also be useful for choosing the right data structures for specific tasks, such as using hash tables for efficient lookups or trees for indexing. The emphasis on time and space complexity analysis is also beneficial, as it helps data engineers make informed decisions about data storage and processing strategies.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts, often working in the finance industry, develop mathematical models and algorithms for trading and risk management. This course serves as a building block for a quantitative analyst, providing a sound base in data structures and algorithmic thinking that's often needed for creating efficient and optimized models. Though quantitative analysis requires a high degree of mathematical and statistical knowledge (often at the graduate level), the ability to implement these models effectively requires a strong understanding of computer science fundamentals. The discussion of time complexity will be invaluable.

See salaries and explore the career path for Quantitative Analyst

Front-End Developer

Front End Developers create user interfaces for websites and applications. While front end development focuses heavily on languages like JavaScript, HTML, and CSS, understanding data structures and algorithms leads to the crafting of more efficient and performant user interfaces. This course helps build a foundation in organizing and manipulating data effectively. In particular, the sections on arrays, matrices, and queues can be useful for managing and displaying data in a user-friendly way. While not the primary focus of front end work, the problem-solving skills honed in this course translate to writing robust and maintainable code.

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Site Reliability Engineer

Site Reliability Engineers ensure the reliability and performance of software systems in production. This course may be helpful for understanding how data structures and algorithms impact system performance. While site reliability engineering focuses on monitoring, automation, and incident response, a solid grasp of fundamental computer science principles aids in troubleshooting performance issues and optimizing system behavior. The course may be useful in identifying potential bottlenecks in code. The knowledge of time and space complexity may be useful for making informed decisions about system configuration and resource allocation.

See salaries and explore the career path for Site Reliability Engineer

Test Engineer

Test Engineers design and implement tests to ensure software quality. Understanding data structures and algorithms may be useful when crafting effective test cases. While test engineering focuses on testing methodologies and tools, a solid grasp of data structures can help in identifying edge cases and writing comprehensive tests that cover different scenarios. This course may be useful for understanding how different data structures behave under various conditions. A test engineer will also find that the problem-solving skills honed in this course translate to identifying and debugging software defects more effectively.

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Engineering Manager

Engineering Managers oversee software development teams, focusing on project management and team leadership. While an Engineering Manager might not write code daily, a strong foundational understanding of computer science principles helps in making informed decisions about project scope, resource allocation, and technical strategy. This course may be useful for reinforcing knowledge of data structures and algorithms. An engineering manager with this training can better assess the complexity and feasibility of different projects. The problem-solving skills honed in this course translate to more effective decision-making and risk management.

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Technical Consultant

Technical Consultants advise clients on technology solutions and help them implement new systems. While a technical consultant role is heavily client-facing, a basic understanding of data structures and algorithms helps in assessing the feasibility and effectiveness of different technology options. This course may be useful for understanding how different data structures and algorithms can be applied to solve real-world business problems. The problem-solving skills honed in this course translate to more effective consulting engagements and better client outcomes.

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Chief Technology Officer

Chief Technology Officers are responsible for a company's overall technology strategy and vision. This course may be useful for reinforcing a background in computer science. While a chief technology officer focuses on high-level strategic decisions, a solid grasp of fundamental computer science principles helps in making informed decisions about technology investments and product development. The CTO will see that the problem-solving skills from this course help with more effective decision-making and risk management.

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Leetcode for Beginners

30 Leetcode Challenge

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What's inside

Learning objectives

Syllabus

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Reviews summary

Beginner's guide to leetcode interviews

Activities

Career center

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