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Codility VS Kaggle

Compare Codility VS Kaggle and see what are their differences

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Contents:
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Codility logo Codility

Codility provides a SaaS platform with advanced validation, security and protection features to evaluate the skills of software engineers.

Kaggle logo Kaggle

Kaggle offers innovative business results and solutions to companies.
  • Codility Landing page
    Landing page //
    2021-07-20

The Codility platform includes:

CodeCheck - Design role-specific remote skills assessments to screen your technical candidates before moving them to the interview stage.

CodeLive - Host technical remote or onsite interviews via our shared editor using a range of templates and whiteboards.

CodeEvent - Assess thousands of candidates at a time via technical recruiting events and find the best talent faster.

  • Kaggle Landing page
    Landing page //
    2023-04-18

Codility features and specs

  • Automated Assessment
    Codility provides automated coding assessments that save time for both recruiters and candidates by quickly identifying technical abilities.
  • Standardized Testing
    Codility offers standardized tests, ensuring evaluations are consistent and unbiased across all candidates.
  • Diverse Question Bank
    The platform has a large repository of coding problems that cover a wide range of topics and difficulty levels, catering to various roles and expertise levels.
  • Real-Time Code Execution
    Codility allows for real-time code execution and validation, enabling candidates to see the results of their code immediately.
  • Customizable Tests
    Recruiters can create custom tests tailored to the specific needs of their company or position, making the assessments more relevant.
  • Detailed Reports
    Codility provides detailed reports and analytics on candidate performance, helping hiring managers to make data-driven decisions.
  • Integration Capabilities
    The platform integrates with various Applicant Tracking Systems (ATS) and other HR tools, streamlining the recruiting process.

Possible disadvantages of Codility

  • Cost
    Codility can be relatively expensive, especially for small companies or startups with limited recruitment budgets.
  • Learning Curve
    There might be a learning curve for both recruiters and candidates to get accustomed to the platform and its features.
  • Language Limitations
    While Codility supports multiple programming languages, some niche or less commonly used languages may not be available.
  • Potential Stress for Candidates
    Automated assessments can induce stress for candidates, which might not accurately reflect their true abilities in a real-world setting.
  • Internet Connection Dependency
    A stable internet connection is required to complete assessments, which can be a limitation in areas with unreliable internet access.
  • Limited Collaboration Features
    Codility's focus on individual assessments means it has limited support for evaluating collaborative or team-based coding skills.
  • Algorithm Focus
    The platform often emphasizes algorithmic problem-solving, which may not fully represent the day-to-day coding skills required for certain positions.

Kaggle features and specs

  • Community
    Kaggle has a vibrant community of data scientists and machine learning practitioners who actively collaborate, share knowledge, and support each other.
  • Competitions
    The platform hosts numerous competitions that allow users to test their skills on real-world problems, often with monetary prizes and recognition.
  • Datasets
    Kaggle offers a vast repository of datasets that are readily available for analysis and can be used to practice and build models.
  • Kernels
    Users can share and run code in the cloud using Kaggle Kernels, which provide a collaborative environment for analysis and model development.
  • Learning Resources
    Kaggle provides numerous tutorials, courses, and micro-courses to help beginners and advanced users improve their skills in data science and machine learning.

Possible disadvantages of Kaggle

  • Steep Learning Curve
    For beginners, the breadth and depth of content and tools available on Kaggle can be overwhelming, making it difficult to know where to start.
  • Competition Pressure
    While competitions can be motivating, they can also be stressful and may require a significant time investment, which can be discouraging for some users.
  • Public Exposure
    Submissions and code are often public, which may not be suitable for all users, especially those uncomfortable with sharing their work or making mistakes publicly.
  • Limited Real-world Application
    Some competitions and datasets are heavily curated or simplified, which may not fully represent the complexities and messiness of real-world data science problems.
  • Resource Limitations
    Free tier users have limited computational resources on Kaggle Kernels, which can be a constraint for more complex models or larger datasets.

Codility videos

+ Add

An Introduction to Codility: The Tech Hiring Platform for Engineering Teams

Kaggle videos

+ Add

How to use Kaggle ?

More videos:

  • Review - Kaggle Live-Coding: Code Reviews! Class imbalanced in Python | Kaggle
  • Review - Kaggle Live-Coding: Code Reviews! | Kaggle

Category Popularity

0-100% (relative to Codility and Kaggle)

Codility

Kaggle

Hiring And Recruitment
100 100%
Hiring And Recruitment
0% 0
Data Collaboration
0 0%
Data Collaboration
100% 100
Online Learning
76 76%
Online Learning
24% 24
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Codility and Kaggle

Codility Reviews

Examining Top 22 Alternatives to LeetCode
Codility is a platform that helps companies assess the coding skills of developers. They offer a range of online coding tests and assessments that enable employers to evaluate candidates' technical abilities.
Source: www.inven.ai

Kaggle Reviews

Top 10 Developer Communities You Should Explore
Kaggle is an online platform that hosts data science competitions, provides datasets for analysis and machine learning projects, and offers a collaborative environment for data scientists and machine learning enthusiasts. It was founded in 2010 and has become a prominent platform for individuals and teams to showcase their data science skills, learn from one another, and...
Source: www.qodo.ai
The Best ML Notebooks And Infrastructure Tools For Data Scientists
Kaggle, an online community of data scientists, hosts Jupyter notebooks for R and Python. Kaggle Notebooks can be created and edited via a notebook editor with an editing window, a console, and a setting window. Kaggle hosts a vast number of publicly available datasets. Besides, you can also output files from a different Notebook or upload your own dataset. Kaggle comes with...
Source: analyticsindiamag.com
Top 25 websites for coding challenge and competition [Updated for 2021]
Kaggle is famous for being the place where data scientists collaborate and compete with each other. But they also have a platform called Kaggle Learn where micro-courses are provided. They are mini-courses where data scientists can learn practical data skills that they can apply immediately. They call it the fastest (and most fun) way to become a data scientist or improve...
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, Kaggle seems to be a lot more popular than Codility. While we know about 101 links to Kaggle, we've tracked only 2 mentions of Codility. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Codility mentions (2)

  • How to Hire Mobile App Developers
    - Technical skills: have they got the walk to match the talk? Programming languages on a resume mean little if candidates are unable to demonstrate their hard coding skills. You can test these skills with technical skill tests, such as the ones created by Codility or HackerRank. - Source: dev.to / about 1 year ago
  • Best Websites Every Programmer Should Visit
    Codility : Verify and improve coding skills. - Source: dev.to / about 4 years ago

Kaggle mentions (101)

  • Machine learning for web developers
    Before you even build a model, you are going to need some kind of dataset. Usually a CSV or JSON file. You can build your own dataset from scratch using your own data, scrape data from somewhere, or use Kaggle. - Source: dev.to / 4 months ago
  • How to Make Money From Coding: A Beginner-Friendly Practical Guide
    Kaggle: For data science and machine learning competitions. - Source: dev.to / 9 months ago
  • Need help with Python / Research Project
    Need help with last minute python project (due today). Project involves choosing a dataset from kaggle.com to analyze and creating questions to answer through analyzing the data. I have a pdf file of the project guidelines if you want more details. Also on a budget. Source: almost 2 years ago
  • Required coding skills needed for DS
    Next, you can do basic analysis of datasets in Python using libraries like pandas and scikit-learn. There's a lot of example datasets on kaggle.com. Source: almost 2 years ago
  • Freelance Working
    Also look into kaggle.com and participate in competitions, etc. This will be something you can show on your CV as real-world-experience while boosting your skills. Source: almost 2 years ago
View more

What are some alternatives?

When comparing Codility and Kaggle, you can also consider the following products

HackerRank - HackerRank is a platform that allows companies to conduct interviews remotely to hire developers and for technical assessment purposes.

Colaboratory - Free Jupyter notebook environment in the cloud.

CodeSignal - CodeSignal is the leading assessment platform for technical hiring.

Numerai - Hedge fund that crowdsources market trading from AI programmers over the Internet

iMocha - Make intelligent talent decisions.

Explorium - Explorium is an External Data Platform that offers ML and AI-based datasets so data scientists can take part in data science competitors and marathons to win prizes.

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