The Bible of Competitive Programming & Coding Interviews from Udemy

This course is going to be your bible on solving each coding interview question and competitive programming challenge. The content is based on my 6 year experience of struggling to find and solve a wide range of problems and develop the system for mastering this skill. I cover the exact same content that has helped my students' performance skyrocket and got them offers at top companies like Google, Facebook and Amazon and solid results in the International Competitive Programming Contests.

We start from basics such as Mathematics Fundamentals: Prime Numbers, Sieve of Eratosthenes, Fast Modular Exponentiation. Then we dive into interesting challenges and gold tricks on arrays and matrices, followed by Binary Search, Recursion and Divide and Conquer. We continue by exploring fundamental data structures such as Stack, Queue, Deque, Heap and Hash Table. Then, after building a solid foundation, we explore complex topics such as Greedy and Dynamic Programming, in which I reveal bulletproof formulas that guide you in solving every single problem of that specific type.

Here's what make this course amazing:

I guide you through the line of my thought when solving each problem, focusing on building the general approach for any type of problem you can encounter in competitive programming contests or software developing interviews.
You will learn all the theory needed, but our main focus here is on practical applications.
I share with you problem solving tricks and good coding practises that took me years and hundreds of problems to figure out.
It's interactive and engaging: I try to keep the theory as simple and natural as possible and we work as a team in solving any problem.

Do you think it's finally the time to get the Software Developer Job or the results in Competitive Programming you deserve? Follow me.

What's inside

Learning objectives

Build a solid foundation to become a competitive programming wizard
Master revolutionary data structures and various types of problems using each of them

Learn fundamental algorithms and solve classical problems
Get ready for codeforces, codechef, hackerrank, acm-icpc and more

Build a solid foundation to become a competitive programming wizard
Master revolutionary data structures and various types of problems using each of them
Learn fundamental algorithms and solve classical problems
Get ready for codeforces, codechef, hackerrank, acm-icpc and more

Syllabus

Know how to take this course

How to take this Course

READ BEFORE YOU START!

What are Algorithms?

Homework: Change the for loop in the code in order for our program to run in O( sqrt(n) ) time complexity.

The solution is in the source code.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers fundamental data structures like Stacks, Queues, and Hash Tables, which are essential for efficient problem-solving in coding challenges

Explores essential algorithms such as Binary Search, Greedy Algorithms, and Dynamic Programming, which are frequently tested in coding interviews

Includes homework assignments to reinforce learning, but solutions are provided, which may discourage independent problem-solving

Teaches C++ STL (Standard Template Library) vectors, maps, and sets, which are powerful tools for efficient coding in competitive programming

Focuses on practical applications and problem-solving tricks, which can be highly beneficial for improving performance in coding contests and interviews

Includes topics like prime number tests and the Sieve of Eratosthenes, which are relevant to number theory problems often found in competitive programming

Reviews summary

Comprehensive guide for competitive programming & interviews

According to learners, this course serves as a comprehensive resource for mastering competitive programming and coding interviews. Many students report it is highly effective in preparing them for technical roles at top companies and improving performance in coding contests. Reviewers frequently highlight the instructor's ability to explain complex topics clearly and his unique approach to problem-solving, focusing on the 'line of thought'. The course is praised for its strong emphasis on practical application and problem-solving techniques rather than just theory. While largely positive, some feedback suggests that having a basic foundation in programming before starting may be beneficial, as the course can be challenging at times.

Better suited for those with some basics.

"I'd recommend having a basic understanding of data structures and algorithms before starting."

"Might be a bit fast-paced if you are an absolute beginner with no prior competitive programming experience."

"Some foundational knowledge is helpful to get the most out of the initial sections."

"It assumes you know some basic programming concepts going in."

Demanding, but leads to deep understanding.

"It can be challenging at times, but pushing through definitely strengthens your understanding."

"This course is not a walk in the park, requires dedicated effort but the reward is immense."

"I found some problems quite difficult initially, which forced me to think harder and learn more."

"While tough, completing the course felt like a real achievement and solidified my skills."

Covers key data structures and algorithms.

"The coverage of Dynamic Programming and Greedy algorithms was particularly helpful."

"Loved the sections on arrays, matrices, and string algorithms."

"The data structures like Heap, Stack, Queue were explained with relevant problems."

"Binary search applications were well demonstrated with multiple problems."

Instructor explains concepts and logic clearly.

"The instructor is great at explaining the thought process behind solving problems step by step."

"The explanations are very clear and easy to follow, even for complex topics."

"I really appreciated how the instructor breaks down the logic during problem-solving sessions."

"His way of explaining difficult concepts made them much more understandable than other resources I've used."

Strong focus on applying concepts to problems.

"Loved the focus on solving actual problems rather than just lecturing on theory."

"The course emphasizes the practical application of algorithms and data structures through numerous examples."

"It teaches you *how* to think about solving problems, not just memorizing solutions."

"The hands-on problem-solving was definitely the most valuable part for me."

Helps prepare for interviews and coding contests.

"The problems covered are highly relevant to what you'd see in coding interviews and competitive programming contests..."

"This course really helped boost my confidence for job interviews and tackling difficult algorithmic problems."

"I feel much better prepared for my upcoming interviews after going through these exercises and explanations."

"It gave me the confidence and skills to tackle competitive programming challenges effectively."

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 The Bible of Competitive Programming & Coding Interviews with these activities:

Review Complexity Analysis

Show steps

Solidify your understanding of complexity analysis to better evaluate and compare algorithms covered in the course.

Browse courses on Complexity Analysis

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Review the definitions of Big O, Big Theta, and Big Omega notations.
Practice determining the time and space complexity of simple code snippets.
Analyze the complexity of common data structure operations.

Review Introduction to Algorithms

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Deepen your understanding of algorithms and data structures with a comprehensive textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Read relevant chapters on data structures and algorithms covered in the course.
Work through the exercises and problems at the end of each chapter.
Compare the book's explanations with the course's explanations.

LeetCode Practice: Arrays and Matrices

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Sharpen your problem-solving skills by practicing array and matrix problems on LeetCode.

Show steps

Solve at least 5 LeetCode problems related to arrays and matrices.
Focus on problems that involve frequency arrays, partial sums, and maximum sum submatrix.
Analyze the time and space complexity of your solutions.

Four other activities

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Show all seven activities

Create a Blog Post on Binary Search

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Solidify your understanding of binary search by explaining the concept and its applications in a blog post.

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Research and gather information on binary search algorithms.
Write a clear and concise explanation of binary search.
Include examples of how binary search is used in different scenarios.
Publish your blog post on a platform like Medium or your personal website.

Implement a Hash Table from Scratch

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Gain a deeper understanding of hash tables by implementing one from scratch.

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Choose a programming language (e.g., Python, Java, C++).
Implement the basic hash table operations: insert, delete, search.
Handle collisions using techniques like chaining or open addressing.
Test your implementation thoroughly with various inputs.

Cracking the Coding Interview

Show steps

Prepare for coding interviews by studying common data structures, algorithms, and problem-solving techniques.

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

Show steps

Read the chapters on data structures and algorithms relevant to the course.
Practice solving the interview questions provided in the book.
Focus on understanding the underlying concepts and problem-solving strategies.

Tutor a Beginner in Data Structures

Show steps

Reinforce your understanding by explaining data structures concepts to someone new to the topic.

Show steps

Find a beginner who needs help with data structures.
Prepare a lesson plan covering basic data structures like arrays, linked lists, and stacks.
Explain the concepts clearly and answer their questions patiently.
Provide practice problems and feedback on their solutions.

Career center

Learners who complete The Bible of Competitive Programming & Coding Interviews will develop knowledge and skills that may be useful to these careers:

Competitive Programmer

A competitive programmer participates in programming contests, solving algorithmic problems under time constraints. This course is explicitly designed to prepare you for competitive programming. The course covers a wide range of topics, including data structures like stacks, queues, and heaps, along with algorithmic techniques such as binary search and dynamic programming. The course's emphasis on problem-solving strategies and coding best practices helps to greatly improve results in competitive programming contests worldwide. If you seek to be a competitive programmer, this course is especially useful.

See salaries and explore the career path for Competitive Programmer

Software Engineer

A software engineer designs, develops, tests, and maintains software applications. Coding interviews and competitive programming challenges are a key part of the hiring process for many software engineering roles. This course, with its focus on mastering data structures and algorithms, prepares you well for these interviews. The course's coverage of topics such as arrays, matrices, binary search, and dynamic programming helps build a strong foundation for solving complex coding problems, which are often encountered in software development roles. This course can help you prepare for your next software engineering role.

See salaries and explore the career path for Software Engineer

Algorithm Developer

An algorithm developer focuses on designing, implementing, and optimizing algorithms for various applications. This course helps build a strong base in algorithms and data structures, which are essential for this role. With modules covering topics like prime numbers, sorting, searching, and dynamic programming, this course provides the tools necessary to approach algorithmic challenges. The emphasis on practical applications and problem-solving found throughout the course helps one cultivate useful skills as an algorithm developer.

See salaries and explore the career path for Algorithm Developer

Full-Stack Developer

A full stack developer works on both the front-end and back-end of web applications. While this course focuses on algorithms and data structures, these are vital for building efficient and scalable back-end systems. The course helps build a solid foundation in computer science concepts. The problem-solving skills taught in the course are valuable for any full stack developer.

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

Game Developer

A game developer designs and creates video games, which involves programming game logic, implementing algorithms, and optimizing performance. This course helps build a solid foundation in data structures and algorithms, which are vital for game development. The course covers topics like arrays, matrices, and search algorithms, which are frequently used in game programming. The problem-solving skills taught in the course prepare you for the challenges of game development. This course helps in the process of becoming a game developer.

See salaries and explore the career path for Game Developer

Robotics Engineer

A robotics engineer designs, builds, and programs robots for various applications. The course's material on data structures and algorithms helps provide you with the tools to solve complex problems in robotics. The study of topics such as graph algorithms, search techniques, and optimization methods is important for developing robot control systems and path planning algorithms. One who wishes to become a robotics engineer may find this to be a helpful course.

See salaries and explore the career path for Robotics Engineer

Data Scientist

A data scientist analyzes large datasets, develops statistical models, and builds machine learning algorithms to extract insights and solve business problems. While this course may not directly cover machine learning, it emphasizes the importance of data structures and algorithms, which are foundational to data science. The course helps build a solid understanding of topics such as arrays, hash tables, and optimization techniques. This course's focus on algorithmic problem-solving helps to provide a necessary foundation for a career as a data scientist.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

A quantitative analyst, often working in the finance industry, develops and implements mathematical and statistical models for pricing, risk management, and trading strategies. This course, concentrating on algorithms and data structures, helps build a strong base for understanding the computational aspects of quantitative finance. The course material on topics like binary search, greedy algorithms, and dynamic programming help one to approach optimization problems in finance. One seeking to become a quantitative analyst may find this course to be valuable.

See salaries and explore the career path for Quantitative Analyst

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models, often needing a strong foundation in algorithms and data structures along with machine learning concepts. This course helps build the foundation in data structures and algorithms needed to understand and implement machine learning algorithms efficiently. The course's coverage of topics such as optimization techniques, data structures, and algorithm design helps to solve complex problems in machine learning. One hoping to become a machine learning engineer can find this to be a helpful course.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

A data engineer builds and maintains the infrastructure for data storage, processing, and analysis. A solid grasp of data structures and algorithms helps to design efficient data pipelines and optimize data processing workflows. The course's coverage of topics such as hash tables, queues, and tree-based structures, and search algorithms can help you become a great data engineer. This course can help you prepare for a data engineer role.

See salaries and explore the career path for Data Engineer

Technical Lead

A technical lead oversees a team of developers, provides technical guidance, and ensures the successful delivery of software projects. While this course does not concentrate on management skills, it helps build a strong foundation in algorithms and data structures, which are essential for providing technical leadership. The course's coverage of problem-solving strategies and coding best practices helps one to make informed decisions and guide their team effectively. The lessons in this course help you become a technical lead.

See salaries and explore the career path for Technical Lead

Research Scientist

A research scientist conducts experiments, analyzes data, and publishes findings in their field of expertise, often requiring a master's degree or doctorate. This course may be useful for building a strong foundation in algorithms and data structures, which are frequently used in scientific computing. The course's coverage of topics such as optimization techniques, graph algorithms, and data analysis helps to solve research problems. This course helps to prepare you for a life as a research scientist.

See salaries and explore the career path for Research Scientist

Systems Architect

A systems architect designs and implements complex software systems, ensuring scalability, reliability, and performance. This course may be useful for learning the foundations of data structures and algorithms, which are essential for designing efficient systems. The course's coverage of topics like data structures, search algorithms, and optimization techniques helps to solve challenges in systems design. One can find that this course helps them prepare for solving problems that systems architects are faced with.

See salaries and explore the career path for Systems Architect

DevOps Engineer

A DevOps engineer automates and streamlines software development and deployment processes. While a DevOps role focuses more on deployment and infrastructure, understanding data structures and algorithms can help you optimize performance and troubleshoot issues. This course helps build a foundation in the fundamentals of computer science. The course's coverage of topics like arrays, queues, and hash tables helps one to be a better DevOps engineer.

See salaries and explore the career path for DevOps Engineer

Database Administrator

A database administrator manages and maintains databases, ensuring data integrity, security, and performance. This course may be helpful for understanding data structures and algorithms, which are important for optimizing database queries and performance. The course's coverage of topics such as hash tables, search algorithms, and indexing techniques helps one to manage large datasets effectively. This course may provide some help in this area.

See salaries and explore the career path for Database Administrator

The Bible of Competitive Programming & Coding Interviews

What's inside

Learning objectives

Syllabus

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Reviews summary

Comprehensive guide for competitive programming & interviews

Activities

Career center

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