Competitive Programming Essentials, Master Algorithms from Udemy

Equip yourself with essential programming techniques required for ACM-ICPC, Google CodeJam, Kickstart, Facebook HackerCup & more. Welcome to Competitive Programming Essentials - the ultimate specialisation on Algorithms for Competitive Coders. The online Competitive Programming Essentials by Coding Minutes is a highly exhaustive & rigorous course on Competitive Programming. The 50+ hours course covers the breadth & depth of algorithmic programming starting from a recap of common data structures, and diving deep into essential and advanced algorithms. The course structure is well-researched by instructors who not only Competitive Coders but have worked with companies like Google & Scaler. This course will help you to get a solid grip of fundamental concepts & comes with practice questions so that you sail through online coding challenges and code-athons with ease. The course is divided into 10 modules and 50 sections covering topics like Mathematics, Number Theory, Bitmasking, Inclusion-Exclusion, Meet in the Middle Techniques, Segment Trees, Fenwick Trees, Square Root Decomposition, Graph Algorithms, Shortest Paths, Game Theory, Pattern Matching, Binary Search, Greedy Techniques, Dynamic Programming and even more.

The problem setters of the course are Siddharth Singhal and Rajdeep Singh. Both are upcoming software developers at Microsoft and Razorpay respectively. They both exhibit excellent knowledge of Data Structures and Algorithms and are avid competitive programmers. Many top companies like Google, Facebook, Amazon, Directi, CodeNation, Goldman Sachs etc encourage Competitive Programming and conduct coding competitions to hire smart people who can solve problems.

Course Highlights

Instructors from Google & Scaler Academy
50+ hours of high quality & structured content
In-depth coverage of all topics
Exhaustive Course Curriculum
Code Evaluation on Coding Exercises
Lifetime Access
Complimentary TA Doubt Support

What's inside

Learning objectives

Understand & implement important techniques in competitive programming
Learn advanced techniques to optimise naive solutions

Ace code-thons and online coding competitons on codeforces, hackerrank
Get ready for acm-icpc, google kickstart, codejam & more

Understand & implement important techniques in competitive programming
Learn advanced techniques to optimise naive solutions
Ace code-thons and online coding competitons on codeforces, hackerrank
Get ready for acm-icpc, google kickstart, codejam & more

Syllabus

Introduction

Course Structure

Exercise Solutions (C++/Java)

Doubt Support

IDE Environment Setup

FAQ's

Learn to use Sublime Text like a Pro for Competitive Coding!

Sublime Setup

Adding Master Header File

Escaping Online Judges

Common Code Snippets

Using Macros

Example Code Explained

Time / Space Complexity Analysis

Space Time Complexity Introduction

Experimental Analysis

Big O Notation

Nested Loops

Note : Edit in Nested Loops - II

Nested Loops - II

Analysis of Bubble Sort

Analayis of BInary Search

Analysis of Merge Sort

Avoiding TLE Errors

Complexities for Worst Case AC

Time/Space Complexity Quiz

Learn to work with important STL Containers.

Data Structures & STL Containers Revisited

Arrays in C++

Array STL

Vector STL

Deque STL

Stack STL

Queue STL

Priority Queue STL

[Webinar] Hashing STL

[Webinar] More on STL

First Unique Character in a String

Kth Largest Element

One Integer

Maximum Score From Removing Stones

Find K Closest Elements

Distinct Candies

Bulls and Cows

Smallest Range Covering Elements from K Lists

Bitmanipulation Basics

Bitwise Operators

Left Shift & Right Shift

Odd Even

Get ith Bit

Clear ith Bit

Set ith Bit

Update ith Bit

Clear Last i Bits

Clear Range of Bits

Replace Bits

Two Power

Power of Four

Decode XORed Array

Count Bits

Count Bits Hack

Make it Binary

Sort Integers by The Number of 1 Bits

Longest Consecutive Run of 1s in Binary

Hamming Distance

Learn to solve Bitmanipulation Problems

Unique Number - I

Unique Number - I Code

Unique Number - II

Unique Number - II Code

Unique Number - III

Unique Number - III Code

Finding Subsequences

Finding Subsets Code

Maximum Score

Triples with Bitwise AND Equal To Zero

Bitwise AND of Range of Numbers

Total Hamming Distance

Travelling Salesman Problem

Travelling Salesman Intution

Travelling Salesman Code

Travelling Salesman - DP Optimisation

Decode Permutation

Shortest Superstring

Big Integers

Welcome!

Introduction to Big Integers

Big Addition Concept

Big Addition Code

Array & Integer Multiplication

Large Factorials

Code Link:
https://ide.codingminutes.com/?id=uty

Code Link:
https://ide.codingminutes.com/?id=nsz

Big Integers in Python

Python's Handling of Big Integers

Big Integer Challenge - Julka

Big Integer Challenge Solution

Learn to compute Nth terms of Linear Recurrences efficiently!

Binary Exponentiation

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers techniques for optimizing naive solutions, which is essential for competitive programming and improving algorithm efficiency

Prepares learners for ACM-ICPC, Google Kickstart, and CodeJam, which are well-known competitive programming contests

Instructors have worked at Google and Scaler, which suggests practical industry experience and relevant insights

Includes code evaluation on coding exercises, which provides hands-on practice and feedback for skill development

Requires familiarity with C++ or Java, which may exclude learners without prior experience in these languages

Teaches Sublime Text setup, which may not be relevant to learners who prefer other IDEs or text editors

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 Competitive Programming Essentials, Master Algorithms with these activities:

Review Data Structures and STL Containers

Show steps

Solidify your understanding of fundamental data structures and STL containers in C++ to prepare for more advanced algorithmic concepts.

Show steps

Review the documentation for each STL container.
Implement basic operations (insert, delete, search) for each data structure.
Solve simple problems using each data structure.

Review 'Introduction to Algorithms' by Cormen et al.

Show steps

Supplement your learning with a deep dive into fundamental algorithms and data structures using a classic textbook.

View Introduction to Algorithms, fourth edition on Amazon

Show steps

Read relevant chapters on topics covered in the course.
Work through the exercises and problems in the book.
Compare the book's explanations with the course materials.

Practice Bit Manipulation Problems

Show steps

Sharpen your bit manipulation skills by solving a variety of problems on platforms like LeetCode or HackerRank.

Show steps

Identify problems that involve bitwise operations.
Solve at least 10 bit manipulation problems of varying difficulty.
Analyze the time and space complexity of your solutions.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Review 'Competitive Programmer's Handbook' by Antti Laaksonen

Show steps

Enhance your competitive programming skills with a handbook tailored for coding competitions.

View Guide to Competitive Programming: Learning and... on Amazon

Show steps

Read chapters on specific algorithms and techniques.
Study the code examples provided in the book.
Apply the techniques to solve practice problems.

Implement a Custom Hash Table

Show steps

Deepen your understanding of hashing by implementing your own hash table with collision resolution strategies.

Show steps

Choose a collision resolution strategy (e.g., separate chaining, open addressing).
Implement the insert, delete, and search operations.
Test your hash table with a large dataset.
Compare the performance of your hash table with STL's unordered_map.

Create a Video Tutorial on Dynamic Programming

Show steps

Solidify your understanding of dynamic programming by creating a video tutorial explaining a specific DP technique or problem.

Show steps

Choose a dynamic programming technique or problem.
Prepare a script and visual aids for your tutorial.
Record and edit your video tutorial.
Share your tutorial with the online community.

Participate in Online Coding Contests

Show steps

Apply your knowledge and skills by participating in online coding contests on platforms like Codeforces, CodeChef, or AtCoder.

Show steps

Register for upcoming coding contests.
Solve as many problems as possible during the contest.
Analyze your performance and learn from your mistakes.

Career center

Learners who complete Competitive Programming Essentials, Master Algorithms 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 Competitive Programming Essentials course is specifically designed for competitive coders, providing comprehensive training in essential programming techniques. The course's rigorous structure, instructors from Google and Scaler Academy, and exhaustive curriculum all contribute to success in competitive coding. The emphasis on ACM-ICPC, Google CodeJam, and similar competitions makes this course a key and direct preparation.

See salaries and explore the career path for Competitive Programmer

Software Engineer

A software engineer designs, develops, tests, and maintains software systems. This Competitive Programming Essentials course helps build a foundation in algorithmic thinking, essential for efficient coding and problem-solving, which are crucial for a software engineer. The course's focus on data structures and algorithms, along with the practice questions, prepares you to tackle complex coding challenges encountered in software development. Specific modules on data structures and STL containers may prove particularly valuable.

See salaries and explore the career path for Software Engineer

Algorithm Developer

An algorithm developer researches, designs, and implements algorithms to solve specific problems. This Competitive Programming Essentials course is directly relevant, as it provides an in-depth understanding of essential and advanced algorithms. The course structure, covering topics such as bitmasking, graph algorithms, and dynamic programming, is tailored to help an algorithm developer to excel. The focus on optimizing naive solutions and tackling online coding competitions translates directly to real-world algorithm design challenges.

See salaries and explore the career path for Algorithm Developer

Embedded Systems Engineer

An embedded systems engineer develops software for embedded systems, such as those found in cars and appliances. This Competitive Programming Essentials course helps building a foundation in algorithmic thinking, essential for optimizing performance in resource-constrained environments. The course's coverage of bit manipulation and data structures is particularly relevant for working with low-level hardware. The understanding of time and space complexity is important for writing efficient code that can run on embedded systems.

See salaries and explore the career path for Embedded Systems Engineer

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models. This Competitive Programming Essentials course helps improve algorithmic skills, which are necessary for optimizing machine learning algorithms and improving model performance. The course's coverage of data structures and algorithms provides a strong foundation for understanding the computational aspects of machine learning. Familiarity with time and space complexity analysis helps with efficient model training and deployment. Specific sections on Dynamic Programming may prove particularly valuable.

See salaries and explore the career path for Machine Learning Engineer

Backend Developer

A backend developer focuses on the server-side logic and databases of web applications. This Competitive Programming Essentials course may be useful by teaching the important skills of problem-solving, algorithm implementation, and application design. The course's structure, covering topics such as bitmasking, graph algorithms, and dynamic programming improves a backend developer's ability to deliver maintainable code. The focus on optimizing naive solutions translates directly to real-world algorithm design challenges.

See salaries and explore the career path for Backend Developer

Research Scientist

A research scientist conducts research to advance knowledge in a specific field. For example, a Research Scientist working on routing algorithms would benefit from this course. This Competitive Programming Essentials course may be useful by strengthening problem-solving skills and algorithmic thinking, which are valuable for developing and testing new algorithms and models. The course's coverage of data structures and advanced algorithms provides a strong foundation for conducting research in computer science. The emphasis on optimizing solutions is essential for developing efficient and scalable algorithms.

See salaries and explore the career path for Research Scientist

Robotics Engineer

A robotics engineer designs, builds, and programs robots for various applications. This Competitive Programming Essentials course helps build a foundation in algorithmic thinking, which is critical for developing efficient robot control systems. The course's coverage of graph algorithms and shortest paths helps design robot navigation algorithms. The course's emphasis on optimizing solutions can lead to more efficient and responsive robot behavior. Specific sections on STL Containers and Dynamic Programming may prove particularly valuable.

See salaries and explore the career path for Robotics Engineer

Data Scientist

A data scientist analyzes large datasets to extract meaningful insights and build predictive models. This Competitive Programming Essentials course may be useful by providing strengthens problem-solving skills and algorithmic thinking, which are valuable for optimizing data analysis processes. The course's coverage of data structures and algorithms helps a data scientist efficiently process and manipulate data. The understanding of time and space complexity analysis also aids in developing scalable data processing pipelines. The modules on STL containers may prove particularly valuable.

See salaries and explore the career path for Data Scientist

Site Reliability Engineer

A site reliability engineer ensures the reliability and performance of software systems in production. This Competitive Programming Essentials course is useful because it builds a foundation in algorithmic thinking, essential for optimizing system performance and troubleshooting issues. The course's coverage of data structures and algorithms helps a site reliability engineer to efficiently analyze system logs and identify performance bottlenecks. Familiarity with time and space complexity analysis aids in diagnosing and resolving scalability issues.

See salaries and explore the career path for Site Reliability Engineer

Quantitative Analyst

A quantitative analyst develops mathematical models for financial analysis and risk management. This Competitive Programming Essentials course can be useful by honing problem-solving skills and algorithmic thinking, which are applicable to developing efficient financial models. The course's coverage of data structures and algorithms provides a foundation for working with financial data and optimizing trading strategies. The emphasis on coding competitions also encourages quick and efficient problem-solving required in the fast-paced finance industry.

See salaries and explore the career path for Quantitative Analyst

Game Developer

A game developer creates video games, designing gameplay mechanics and implementing game logic. This Competitive Programming Essentials course may be useful by strengthening algorithmic skills, which are crucial for optimizing game performance. The course's modules on graph algorithms and dynamic programming help create efficient game AI and pathfinding algorithms. The training in problem-solving under time constraints prepares one to handle the real-time challenges of game development. Specific sections in Game Theory may prove particularly valuable.

See salaries and explore the career path for Game Developer

Full-Stack Developer

A full stack developer works on both the front-end and back-end of web applications. This Competitive Programming Essentials course may be useful by strengthening general problem solving abilities. The course's treatment of data structures, and algorithms helps a developer implement robust and efficient application programming interfaces. The practice solving online coding challenges is relevant because a full stack developer may be responsible for solving real-world problems in the software domain.

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

DevOps Engineer

A DevOps engineer automates and streamlines software development and deployment processes. This Competitive Programming Essentials course can be useful by strengthening algorithmic thinking, which helps in optimizing deployment pipelines and automating infrastructure management. The course's coverage of data structures and algorithms provides a foundation for developing efficient automation scripts. The training in problem-solving under time constraints prepares you to handle real-time deployment challenges. Specific modules on STL containers may prove particularly valuable.

See salaries and explore the career path for DevOps Engineer

Cybersecurity Analyst

A cybersecurity analyst protects computer systems and networks from cyber threats. This Competitive Programming Essentials course may be useful by strengthening problem-solving skills and algorithmic thinking, which are valuable for analyzing malware and detecting vulnerabilities. The course's coverage of bit manipulation and data structures provides a foundation for understanding low-level security exploits. Specific modules on pattern matching may prove particularly valuable.

See salaries and explore the career path for Cybersecurity Analyst

Reading list

We've selected two 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 Competitive Programming Essentials, Master Algorithms.

Introduction to Algorithms, fourth edition

Save

Comprehensive textbook on algorithms, covering a wide range of topics relevant to competitive programming. It provides detailed explanations, pseudocode, and analysis of various algorithms and data structures. It valuable resource for understanding the theoretical foundations of algorithms and improving problem-solving skills. This book is commonly used as a textbook in undergraduate and graduate computer science programs.

Introduction to Algorithms, fourth edition

Hardcover

$$$$

Introduction to Algorithms, fourth edition

Kindle Edition

$$$

Guide to Competitive Programming

Save

This handbook provides a concise and practical guide to competitive programming. It covers essential algorithms and data structures with a focus on implementation and optimization. It also includes tips and tricks for solving problems efficiently. great resource for quickly learning and applying common techniques.

Guide to Competitive Programming: Learning and...

Paperback

$$$

Competitive Programming Essentials, Master Algorithms

What's inside

Learning objectives

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

Share

Similar courses