Beat the Codility Coding Interview in Python from Udemy

This course has been designed to help you pass your next coding interview. It focuses on puzzles from Codility's training lessons, so if you have an online coding test coming up, this course is perfect for you.

The key to passing coding interviews is to practice as much as possible by solving various types of coding puzzles. In doing so you sharpen your problem solving skills and eventually you will start to see patterns amongst the different coding solutions. You also increase your chances of being asked a problem you’ve already solved.

In this course you’ll get to practice many of these coding puzzles. In every section we introduce the topic, explain the problem and later provide you with a few hints that help solve the puzzle. In the end we arrive at the solution together.

Along the way you'll learn how to ride a motorbike, surf, scuba dive and fly an aeroplane. *

Join me on this course, and let’s get you to pass this interview.

*Not really, however this course is pretty fun regardless.

All code in this course can be found on github, username/project: cutajarj/CodilityInPython

What's inside

Learning objectives

Experience solving many of codility's coding interview puzzles, with problem descriptions, hints and solutions
Learn common problem solving tips ideal for coding interviews in python

Have a greater chance of passing the coding interview with codility, hackerrank and others

Experience solving many of codility's coding interview puzzles, with problem descriptions, hints and solutions
Learn common problem solving tips ideal for coding interviews in python
Have a greater chance of passing the coding interview with codility, hackerrank and others

Syllabus

Quick recap on Complexity Theory

Introduction

Make most of this course

Useful links and resources

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Focuses on puzzles from Codility's training lessons, which is directly relevant for learners preparing for online coding tests and technical interviews

Teaches common problem-solving tips ideal for coding interviews in Python, which is a widely used language in software development and technical roles

Explores complexity theory, arrays, stacks, queues, sorting, and other fundamental data structures and algorithms, which are essential for coding interviews

Includes code walkthroughs for each problem, which can help learners understand the solutions and improve their coding skills

Covers topics like prefix sums, primes and composites, and the Euclidean algorithm, which may be useful for more advanced problem-solving scenarios

Provides hints for each problem, which can guide learners towards the solution without giving it away completely, promoting independent problem-solving skills

Reviews summary

Effective practice for coding interviews

According to students, this course is a highly effective resource for preparing for coding interviews, particularly those involving platforms like Codility. Learners praise the clear explanations, well-chosen practice problems, and practical Python solutions. The structure, which moves from problem description to hints and then the solution, is also frequently highlighted as helpful. Some students report they even passed their interviews after taking the course. However, a minority of reviewers found some explanations to be rushed or not deep enough, suggesting the course might be too basic for experienced learners or that supplemental resources may be needed.

Instructor breaks down concepts clearly.

"The explanations are clear and concise, and the code walkthroughs are easy to follow."

"The instructor does a great job breaking down the logic."

"Solid explanations for most problems. The structure is helpful..."

"Good course, helped me brush up... Explanations are mostly clear."

Problems are well-chosen for interview preparation.

"The problems selected are very representative of what you might encounter in a real Codility test."

"Passed my Codility test thanks to this course! The practice problems were spot on."

"Excellent course for interview preparation. The problems are well-chosen..."

"Highly effective for targeting Codility interviews. The approach of solving problems... is great."

May require supplements or be basic for some.

"Found the course too basic. If you have some experience... this might not be challenging enough."

"Some explanations felt a bit rushed, and I sometimes had to look up additional resources..."

"...not a complete solution."

"...Could perhaps benefit from a bit more focus on time/space complexity analysis..."

"The explanations for more complex problems were not deep enough."

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 Beat the Codility Coding Interview in Python with these activities:

Review Data Structures and Algorithms

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Reinforce your understanding of fundamental data structures and algorithms before diving into Codility problems. This will provide a solid foundation for problem-solving.

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Review common data structures like arrays, linked lists, stacks, and queues.
Practice implementing basic algorithms such as searching and sorting.
Solve introductory problems on platforms like LeetCode or HackerRank.

Review 'Grokking Algorithms'

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Use 'Grokking Algorithms' to build a strong foundation in algorithms before tackling Codility problems. This will make it easier to understand the underlying concepts and develop effective solutions.

View Grokking Algorithms, Second Edition on Amazon

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Read the chapters on fundamental algorithms like searching, sorting, and graph algorithms.
Work through the examples and exercises in the book.
Apply the concepts you learned to solve Codility problems.

Review 'Cracking the Coding Interview'

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Supplement your Codility practice with 'Cracking the Coding Interview' to gain a broader understanding of coding interview concepts and strategies. This will help you tackle a wider range of problems.

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

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Read the relevant chapters on data structures and algorithms.
Solve the practice problems at the end of each chapter.
Compare your solutions with the book's solutions and identify areas for improvement.

Four other activities

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Show all seven activities

Solve Codility Lesson Problems

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Practice solving problems from Codility's lessons to build familiarity with the platform and common problem types. This will improve your speed and accuracy.

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Choose a Codility lesson (e.g., Arrays, Stacks and Queues).
Attempt to solve each problem in the lesson independently.
Analyze the provided solutions and identify areas for improvement.

Participate in Peer Coding Sessions

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Collaborate with peers to solve Codility problems and discuss different approaches. This will expose you to new perspectives and improve your communication skills.

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Find a study partner or join a coding group.
Choose a Codility problem to solve together.
Discuss your solutions and provide constructive feedback.

Create a Video Explanation of a Codility Problem

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Solidify your understanding of a Codility problem by creating a video explanation of the problem, your solution, and the reasoning behind it. This will force you to articulate your thought process clearly.

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Select a Codility problem you have solved.
Record a video explaining the problem statement, your solution, and the time complexity.
Share your video with others and solicit feedback.

Build a Codility Problem Solver

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Develop a tool that automatically solves Codility problems based on input parameters. This will challenge you to apply your knowledge in a practical setting.

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Choose a set of Codility problems to support.
Implement algorithms to solve the problems automatically.
Test your solver and refine its performance.

Career center

Learners who complete Beat the Codility Coding Interview in Python will develop knowledge and skills that may be useful to these careers:

Software Engineer

A Software Engineer designs, develops, and tests software applications. This course, focused on mastering coding interview puzzles using Python, directly contributes to success in this role. The puzzles covered in this course, such as those addressing arrays, counting elements, stacks, queues, and sorting, provide a solid foundation in data structures and algorithms which helps solve real world software problems. By practicing with problems similar to those found on platforms like Codility and HackerRank, this course equips aspiring Software Engineers with the skills and confidence needed to excel in technical interviews and secure their desired position.

See salaries and explore the career path for Software Engineer

Algorithm Engineer

An Algorithm Engineer focuses on designing and implementing efficient algorithms. This course, centered around preparing for coding interviews by solving Codility puzzles using Python, is highly relevant. The course provides hands-on experience with a wide range of algorithmic problems, including those related to arrays, stacks, queues, sorting, and greedy algorithms. By working through these puzzles, and learning common problem-solving tips, learners develop a deeper understanding of algorithmic principles. The course's emphasis on algorithmic problem-solving makes it an invaluable resource for those seeking to excel as an Algorithm Engineer.

See salaries and explore the career path for Algorithm Engineer

Backend Developer

A Backend Developer works on the server-side logic and databases that power applications. Excelling in coding interviews often involves demonstrating proficiency in data structures and algorithms, which this course directly addresses. The course covers several data structures and algorithms such as arrays, stacks, queues, sorting etc. The course's practical approach to solving coding puzzles, similar to those encountered in technical interviews, equips aspiring Backend Developers with the skills and confidence needed to succeed in their job search and on the job.

See salaries and explore the career path for Backend Developer

Technical Consultant

A Technical Consultant advises clients on technology solutions. This course, focused on solving coding interview puzzles using Python, contributes to success in this role. The puzzles covered in this course, such as those addressing arrays, counting elements, stacks, queues, and sorting, provide a solid foundation in data structures and algorithms which helps communicate the value of certain solutions. Technical consultants are trusted experts who are expected to be able to understand any technology or architecture on a deep level. By practicing with problems similar to those found on platforms like Codility and HackerRank, this course equips aspiring Technical Consultants with the skills and confidence needed to excel.

See salaries and explore the career path for Technical Consultant

Full-Stack Developer

A Full Stack Developer works on both the front-end and back-end of web applications. This course, which aims to help individuals pass coding interviews by focusing on Python and problem-solving skills, is beneficial. Full stack development requires proficiency in algorithms and data structures to optimize application performance. The course's coverage of algorithmic techniques, such as sorting, searching, and dynamic programming, helps build a strong foundation for tackling the technical challenges encountered in full stack roles. For those seeking to enhance their problem-solving abilities and coding skills, this course may be useful.

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

Software Development Engineer in Test

A Software Development Engineer in Test (SDET) writes code to test software and ensure its quality. This course, which focuses on passing coding interviews by practicing with Python puzzles, is valuable. Being able to write efficient tests often means being able to leverage concepts such as time complexity. The course may help SDETs with their problem-solving skills which can transfer to the job of writing tests. By working through this course, individuals are more likely to be well-prepared for the coding components of interviews and the demands of the job.

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

Quantitative Analyst

A Quantitative Analyst, often working in the finance industry, builds mathematical models and algorithms for trading and risk management. This course, which focuses on solving coding interview puzzles in Python, builds a strong foundation in algorithmic thinking and problem-solving. Quantitative roles often require very quick thinking in a fast paced environment, as well as the ability to work under pressure. The course covers topics such as sorting, prefix sums, and greedy algorithms, all relevant to quantitative analysis. The practice with Codility-style problems can effectively prepare individuals for the coding challenges encountered in quantitative finance roles.

See salaries and explore the career path for Quantitative Analyst

Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. This course emphasizing coding interview preparation through Python-based puzzle solving, helps build essential problem-solving skills. Machine learning engineering requires strong coding abilities to implement and optimize algorithms. The course's coverage of algorithmic techniques, such as sorting, prime number identification, and greedy approaches, equips individuals with a practical understanding of fundamental concepts. The hands-on practice with coding puzzles helps in preparing for the technical challenges inherent in machine learning engineering.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist uses programming to analyze and interpret complex datasets, often requiring advanced problem-solving skills. This course, designed to help individuals pass coding interviews through extensive practice with coding puzzles in Python, can be valuable. The course's focus on problem-solving techniques, including complexity theory and various algorithmic approaches such as greedy algorithms, sorting, and prefix sums, helps build a strong foundation for efficiently manipulating and extracting insights from data. For those seeking to enhance their coding skills for data analysis and modeling, this course may be useful.

See salaries and explore the career path for Data Scientist

Research Scientist

A Research Scientist conducts research and experiments, often requiring advanced programming skills. This course, designed to help individuals pass coding interviews through extensive practice with coding puzzles in Python, helps build essential problem-solving abilities. Research often involves implementing and testing algorithms. The course's focus on problem-solving techniques, including complexity theory and various algorithmic approaches such as greedy algorithms, sorting, and prefix sums, helps build a strong foundation for efficiently implementing and validating models. The course prepares those seeking to enhance their coding skills for research roles particularly suited to those holding a Master's or PhD degree.

See salaries and explore the career path for Research Scientist

Data Engineer

A Data Engineer builds and maintains the infrastructure for data storage and processing. This course, centered around preparing for coding interviews by solving Codility puzzles using Python, can be valuable. Data engineering often involves writing scripts and programs to transform and load data, requiring strong coding skills. The course's coverage of algorithmic techniques, such as sorting, searching, and dynamic programming, helps build a strong foundation for tackling the technical challenges encountered in data integration and pipeline development. For those seeking to enhance their problem-solving abilities and coding skills, this course may be useful.

See salaries and explore the career path for Data Engineer

DevOps Engineer

A DevOps Engineer automates and streamlines software development and deployment processes. While not directly related to infrastructure management, this course, designed to help individuals pass coding interviews through Python-based problem-solving, builds valuable coding and algorithmic skills. DevOps roles often require scripting and automation, which benefit from a solid understanding of data structures and algorithms. The course's emphasis on problem-solving techniques, such as sorting, searching, and dynamic programming, allows DevOps engineers to be able to work quickly and efficiently. The coding course may also be useful for diagnosing problems and troubleshooting code.

See salaries and explore the career path for DevOps Engineer

Security Engineer

A Security Engineer protects computer systems and networks from threats. This course aims to enhance your coding interview performance focusing on Python puzzles from Codility's training lessons. While security engineering involves many specialized skills, a strong foundation in coding and problem-solving is essential. The course's coverage of topics such as complexity theory, arrays, and sorting may be useful in the design of security structures. The course may also be useful in writing scripts and programs to automate security tasks. For those seeking to enhance their coding abilities, this course may be useful.

See salaries and explore the career path for Security Engineer

Technical Lead

A Technical Lead guides a team of developers. This course, designed to help you pass your next coding interview focusing on Python puzzles from Codility's training lessons, may be useful. Technical Leads often need to be able to jump in and assist with code reviews, debugging, and complex problem-solving. The course's focus on topics such as complexity theory, arrays, stacks, queues and sorting helps build a strong foundation for efficiently manipulating, understanding, and explaining code. For those seeking to enhance their coding skills, this course may be useful.

See salaries and explore the career path for Technical Lead

Database Administrator

A Database Administrator (DBA) manages and maintains databases. This course, which focuses on helping individuals pass coding interviews using Python, builds valuable problem-solving skills. DBAs often need to write queries and scripts to manage database performance and troubleshoot issues. The course may help when creating well optimized database queries. While not directly related to database administration, this course helps aspiring DBAs with the problem-solving skills required on the job.

See salaries and explore the career path for Database Administrator

Beat the Codility Coding Interview in Python

What's inside

Learning objectives

Syllabus

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Reviews summary

Effective practice for coding interviews

Activities

Career center

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