Competititve Programming & Coding Interviews

This course is going to be your bible on solving each coding interview question and competitive programming challenge. The content is based on my 9 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.

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 coding 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 practices 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

Arrays, Strings & Sorting

Longest Common Prefix

Maximum Value And Number Of Occurences

Maximum Consecutive Ones

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers data structures and algorithms, which are essential for coding interviews and competitive programming, providing a strong foundation for tackling complex problems

Focuses on practical applications and problem-solving tricks, which can help learners develop a more intuitive understanding of how to approach coding challenges

Includes topics like backtracking, stacks, two pointers, sliding window, graphs, hash maps, and greedy algorithms, which are frequently encountered in coding interviews

Uses Python, a popular language in both industry and competitive programming, making the skills learned directly applicable to real-world scenarios

Explores nested loops and brute force algorithms, which are important for understanding time complexity and optimizing solutions, but may not always be the most efficient approach

Features content based on the instructor's experience, which may reflect a specific problem-solving style that might not suit all learners

Reviews summary

Coding interviews & competitive programming

According to learners, this course is designed as a fundamental guide for tackling competitive programming challenges and coding interviews using Python. Students report that it provides a solid foundation covering essential data structures and algorithms through a practical, problem-solving approach. The course structure, featuring numerous solved problems, is seen as a major strength for building the necessary skills for platforms like Codeforces and preparing for roles at top tech companies.

Comprehensive coverage of core CS topics.

"The syllabus covers all the crucial algorithms and data structures you need."

"I learned about Arrays, Graphs, Dynamic Programming (inferred based on problems) and more."

"It provides a good overview of fundamental concepts needed for coding challenges."

"Getting a solid grasp of data structures like Hash Maps and Linked Lists here was key."

Builds skills for competitive programming.

"This course is a great starting point for getting into competitive programming."

"It covers the types of problems you see on platforms like Codeforces and HackerRank."

"Learning the thought process for contests was a key takeaway for me."

"Helped me understand the basic algorithms needed for competitive events."

Strong emphasis on solving real problems.

"This course really helped me focus on the practical application of algorithms and data structures."

"I appreciate the way the course goes through solving actual coding problems step-by-step."

"The large number of problem examples provided is extremely helpful for practice."

"I found the problem-solving approach taught in the course very useful for interviews."

Directly applicable to coding interviews.

"This course is specifically tailored for coding interviews at top tech companies."

"I feel much more prepared for my upcoming interviews after taking this course."

"The focus on problem-solving strategies is directly relevant to the interview process."

"Perfect for anyone getting ready to apply for developer jobs."

Could be challenging without basics.

"Some parts might be difficult if you're not already familiar with Python or basic programming."

"It moves quickly, so having a foundation helps a lot."

"Beginners might need to supplement with other resources to fully grasp concepts."

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 Competititve Programming & Coding Interviews - Python with these activities:

Review Python Fundamentals

Show steps

Strengthen your Python foundation to better understand the code examples and implement solutions in the course.

Browse courses on Python Syntax

Show steps

Review basic Python syntax and data types.
Practice writing simple functions and classes.
Work through basic Python tutorials or exercises.

Review 'Cracking the Coding Interview'

Show steps

Supplement the course material with a widely-used resource for coding interview preparation.

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

Show steps

Read relevant chapters on data structures and algorithms.
Solve practice problems from the book.
Compare your solutions with the book's solutions.

Solve Array and String Problems on LeetCode

Show steps

Reinforce your understanding of arrays and strings by solving problems on LeetCode.

Show steps

Select a set of array and string problems on LeetCode.
Attempt to solve each problem independently.
Analyze the time and space complexity of your solutions.
Compare your solutions with optimal solutions.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Implement a Graph Traversal Algorithm Visualizer

Show steps

Solidify your understanding of graph traversal algorithms by building a visualizer.

Show steps

Choose a graph traversal algorithm (e.g., BFS, DFS).
Design a user interface for visualizing the graph.
Implement the chosen algorithm in Python.
Integrate the algorithm with the visualizer.

Create a Video Explaining Dynamic Programming

Show steps

Deepen your understanding of dynamic programming by creating a video tutorial.

Show steps

Choose a dynamic programming problem to explain.
Prepare a script and visuals for the video.
Record and edit the video.
Share the video with others and gather feedback.

Review 'Introduction to Algorithms'

Show steps

Enhance your understanding of algorithms with a classic textbook.

View Introduction to Algorithms, fourth edition on Amazon

Show steps

Read chapters on specific algorithms covered in the course.
Work through exercises and examples in the book.
Compare the book's explanations with the course material.

Contribute to a Competitive Programming Library

Show steps

Apply your skills and contribute to the open-source community by working on a competitive programming library.

Show steps

Find an open-source competitive programming library on GitHub.
Identify a bug or feature to work on.
Implement the fix or feature and submit a pull request.
Respond to feedback and revise your contribution.

Career center

Learners who complete Competititve Programming & Coding Interviews - Python will develop knowledge and skills that may be useful to these careers:

Competitive Programmer

A competitive programmer participates in programming contests, solving complex algorithmic problems under time constraints. This course is essentially designed for individuals aspiring to excel in competitive programming. The course focuses on building a solid foundation to become a competitive programming wizard, and mastering data structures, fundamental algorithms, and various problem-solving techniques can enhance your performance in contests like Codeforces, CodeChef, and ACM-ICPC. The course's emphasis on practical application is perfect for a competitive programmer.

See salaries and explore the career path for Competitive Programmer

Software Engineer

A software engineer designs, develops, and tests software applications. This course is directly relevant, as it focuses on mastering coding interview questions and competitive programming challenges, which are crucial for landing a software engineering role. The course emphasizes practical applications, problem-solving tricks, and efficient coding practices, all of which are essential skills for a software engineer. Mastering data structures, fundamental algorithms, and various problem-solving techniques, can significantly improve a software engineer's ability to design robust and scalable software solutions.

See salaries and explore the career path for Software Engineer

Algorithm Developer

An algorithm developer creates and implements algorithms for various applications, such as search engines, data analysis, and artificial intelligence. This course emphasizing algorithms makes it highly relevant. By learning fundamental algorithms and mastering data structures, you will be equipped to design and optimize algorithms for complex problems in different fields. This course's focus on practical applications ensures that an algorithm developer can implement these algorithms effectively.

See salaries and explore the career path for Algorithm Developer

Full-Stack Developer

A full stack developer is proficient in both front-end and back-end development, building complete web applications. While this course doesn't directly cover front-end technologies, it strengthens your problem-solving and algorithmic skills, which are valuable for any developer. The ability to efficiently solve problems and implement complex logic is crucial for back-end development, and also helps a full stack developer in designing efficient and scalable applications. The course's focus on data structures and algorithms can help a full stack developer write better code.

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

Game Developer

A game developer designs, develops, and tests video games. This course is valuable, as it builds a strong foundation in algorithms and data structures, which are essential for game development. The ability to efficiently implement game mechanics, optimize performance, and solve complex problems is crucial for a game developer. The focus on problem-solving in this course can help game developers create engaging and immersive gaming experiences.

See salaries and explore the career path for Game Developer

Data Scientist

A data scientist analyzes large datasets to extract insights and build predictive models. While this course doesn't cover statistical analysis directly, it helps build a foundation in algorithmic thinking and problem-solving, which are very relevant for a data scientist. The ability to efficiently process data and implement algorithms is crucial for data preprocessing, feature engineering, and model optimization. A data scientist can also use the data structures knowledge to write efficient code.

See salaries and explore the career path for Data Scientist

Software Development Engineer in Test

A software development engineer in test designs and develops automated tests for software applications. This course may be useful, as it helps develop strong problem-solving skills and a deep understanding of algorithms, both of which are valuable for writing effective test cases. The course's emphasis on practical application can help a software development engineer in test design robust and efficient test suites that can cover edge cases and uncover potential bugs in the software.

See salaries and explore the career path for Software Development Engineer in Test

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models. This course may be helpful, as it provides a foundation in algorithms and data structures, which are important for understanding and implementing machine learning algorithms. Though it does not cover machine learning concepts directly, the skill set developed includes the ability to solve complex problems, which is critical in machine learning engineering, where optimizing algorithms is a common task. Understanding data structures can also help a machine learning engineer handle data more efficiently.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

A quantitative analyst, often working in finance, develops and implements mathematical models for pricing securities, managing risk, and identifying trading opportunities. This course helps build a strong foundation in algorithmic thinking and problem-solving, which is relevant for a quantitative analyst. The ability to efficiently implement complex mathematical models and analyze large datasets is essential. The course's focus on data structures and algorithms can help a quantitative analyst optimize their code and improve performance.

See salaries and explore the career path for Quantitative Analyst

Database Administrator

A database administrator manages and maintains databases, ensuring data integrity, security, and availability. While this course does not directly cover database management systems, it helps develop strong problem-solving skills and a deep understanding of data structures, which are useful for optimizing database performance. A database administrator might find the algorithms taught to be helpful when writing code.

See salaries and explore the career path for Database Administrator

Technical Lead

A technical lead guides and mentors a team of developers, providing technical direction and ensuring the successful delivery of projects. This course may be useful, as it enhances problem-solving skills and provides a deeper understanding of algorithms, which can help a technical lead make informed decisions. The ability to quickly identify and resolve technical challenges is critical for a technical lead, and the problem solving can help them become an effective leader.

See salaries and explore the career path for Technical Lead

Technology Consultant

A technology consultant advises clients on how to use technology to meet their business goals. This course may be useful, as it helps develop strong problem-solving skills and provides exposure to various algorithmic approaches, which can help a technology consultant provide effective recommendations to clients. The ability to quickly assess client needs and propose innovative solutions is crucial for a technology consultant. One should expect to pursue an advanced degree.

See salaries and explore the career path for Technology Consultant

Site Reliability Engineer

A site reliability engineer ensures the reliability and performance of software systems. This course may be useful, as it helps develop a strong foundation in algorithms and data structures, which can be applied to optimize system performance and troubleshoot issues. The course's focus on practical application can help a site reliability engineer develop automated solutions for monitoring and maintaining the reliability of complex systems. One should expect to pursue an advanced degree.

See salaries and explore the career path for Site Reliability Engineer

IT Manager

An IT manager is responsible for the planning, coordination, and direction of all computer-related activities within an organization. While this course might not directly relate to the managerial aspects of the role, it enhances the problem-solving skills that are helpful when addressing technical challenges. Having a solid foundation in computer science can enable an IT manager to make more informed decisions.

See salaries and explore the career path for IT Manager

Project Manager

A project manager is responsible for planning, executing, and closing projects. While this course is not directly related to project management methodologies, the problem-solving skills and logical thinking developed are transferrable. For example, the ability to break down complex problems into smaller, manageable tasks is essential for project planning and execution. This course can help a project manager approach challenges more efficiently and effectively.

See salaries and explore the career path for Project Manager

Competititve Programming & Coding Interviews - Python

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Coding interviews & competitive programming

Activities

Career center

Reading list

Share

Similar courses