Does Kaggle allow the users to download the course materials?

While video lessons and quizzes are only accessible online, Kaggle allows learners to download the notebooks and use their favorite Jupyter IDE (e.g.: VS Code, Jupyter Lab, JetBrains Datalore, Google Colab, AWS Sagemaker). These downloadable resources are helpful for learners who want to continue practising even when not connected to the internet.

Are Kaggle courses free?

Yes, all Kaggle courses are completely free. Kaggle does not charge for access to any of its courses, quizzes, or coding exercises. This makes Kaggle an excellent platform for learners who want to gain data Science and machine learning skills without any financial investment. The only requirement is that you create a Kaggle account to start accessing the courses.

Where can I check my Kaggle certificates from?

After you complete a course, navigate to the Kaggle Learn Courses homepage. You should see two tabs: Active and Completed. Click on Completed. Every course you have completed should now appear in the course listing, along with a View Certificate button that navigates to your certificate.

What is the format of Kaggle courses?

Kaggle courses are designed to be engaging and practical. They include: Video Lessons: Pre-recorded videos explaining the key concepts in an easy-to-understand manner. Quizzes: Quizzes will test your understanding and reinforce learning. Coding Exercises: These exercises allow you to practice what you've learned by writing code in an interactive environment directly within the course platform. Projects: Practical, hands-on projects where you can apply concepts to solve real-world problems. Notebooks: Kaggle courses often provide interactive Jupyter Notebooks, which learners can use to run and modify code.

Kaggle Data Visualization Courses & Certifications Online

4.6 /5

(80 Ratings)

Kaggle Overview

Table of contents

Kaggle All courses
Kaggle Student reviews

Kaggle
All courses

Search by Courses, Specialization

Streams

Course

Mode of Study

Specialization

5 More

Showing 1 Course

Data Visualization

Certificate

5.0

Total Fees

Free

Duration

4 hours

Difficulty level

– / –

Skills

Python Data visualization

Commonly asked questions
On All Courses

Q: Can I use Kaggle courses to prepare for competitions?

Yes! Kaggle courses are designed to help learners prepare for competitions. The courses cover key topics for participating in Kaggle competitions, such as data preprocessing, feature engineering, and model evaluation. By applying the techniques learned in the courses, learners can develop the skills to build strong models and perform well in Kaggle challenges.

Q: How do I enroll in Kaggle courses?

Enrolling in Kaggle courses is simple. Follow below steps -

Create a free account on Kaggle.
Navigate to the "Learn" section once logged in.
Browse through the available courses and pick the one that interests you.
Enrollment is instant, and you can start accessing the course content immediately.

Q: How long does it take to complete a Kaggle course?

Most Kaggle courses are short and designed to be completed in a few hours, especially those on fundamentals. However, learners can take as much time as they need to grasp the material, as the courses are self-paced fully. Some advanced topics, like deep learning, may take longer to complete, especially if you spend additional time practising and implementing the techniques on real-world datasets.

Q: Do Kaggle provide certificates on completion of courses?

Yes, Kaggle provides certificates of completion for each course. After completing a course, learners can download and share the certificate, which can be added to resumes, LinkedIn profiles, and personal portfolios. These certificates can help demonstrate a learner's data Science or machine learning skills to potential employers or colleagues.

Kaggle
Students Ratings & Reviews

4.6/5

80 Ratings

4-5
25
3-4
13
2-3
2

Hemkumar Vipulbhai Bhavsar

Python

Learning Experience: course content is good, platform is very user friendly and there is five questions after every module so the challenges of the course are very helpful for concepts.

Faculty: This course is self-learning based there is no faculties. The course curriculum is very simple understandable for beginners.

Reviewed on 4 Mar 2023Read More

Ramanan

Python

Learning Experience: It was a very good platform to learn python as well as other programming languages. We can use hint if we want and we can also view solutions for the problems if we have vo idea

Faculty: It's a self interest platform and if you are loyal, you can gain knowledge The questions are really thinkable and creative. I like the way the questions are explained. That looks professional

Reviewed on 3 Mar 2023Read More

siddheshwar paikroy

Data Cleaning

Learning Experience: It has quality content that is enough to start working on projects.

Faculty: It is self learning course, you have to read the content provided and do some exercises correctly to proceed to other modules. it contains well designed modules which have cintent that focuses on the job to be done but most efficiently.

Course Support: It is one of the pre requisites required for the job profile

Reviewed on 25 Feb 2023Read More

Bhushan Karma

Python

Learning Experience: The course is quite structured and easy to grasp.one can easily understand the concepts through various practice labs and practice sets. There are realword projects too.

Faculty: The faculty is quiet good and they have met good and structured material .learning through peer graded assignment is quite fun and a good learning experience Each concept comes with their own assesments and assignments. IBM platform is really good for programming and data science

Course Support: The course had impact from basic to advance level which makes it a complete guide to learn data science

Reviewed on 19 Feb 2023Read More

siddheshwar paikroy

Python

Learning Experience: The topics covered are enough and to the point for data analytics.

Faculty: so it is basically DIY course it's basically python coding and how to optimise the code

Course Support: learnt about new libraries and some new concepts

Reviewed on 11 Feb 2023Read More

Saraswati Tiwari

Intro to Machine Learning

Learning Experience: This course is from Kaggle which is a large community. There is a tutorial plus excercise to do where we build our first machine learning model. In this course we learn about Model Validation, Undercutting and Overfitting & Random Forests. And in last there is a machine learning competition.

Faculty: Faculty is very cooperative... After completing the course we will gain a certificate of this course by the instructor. Here we gain a practical knowledge. This course is free of cost. In this course we learn about to build ML models.

Course Support: Very supportive

Reviewed on 28 Jan 2023Read More

View All 17 Reviews