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Role of Kaggle in Pursuing Data Science as a Field of Study

3 Mins read

Practice on Kaggle to enhance your knowledge in data science by earning practical experience

The best way to learn coding and data science is by practicing it with as many assignments as possible. Moreover, it is a boon if that comes with practicing on Kaggle with professionals. Kaggle has been serving aspirants of data science sincerely for the last 11 years. Precisely, a platform that brings together millions of data science practitioners, as well as professionals, has to be appreciated for the great array of opportunities it extends. Kaggle as a subsidiary data science company of Alphabet has grown rapidly in the last few years. This signifies the fervour to learn data science in the learners today. Data science education is pervading enormously across the world and many software are appearing on the forefront claiming to be helping the seekers of data science.

Kaggle is one of the platforms that is serving diligently in shaping future data scientists. With the extraordinary technique of imparting students with data science knowledge, Kaggle has employed various disciplines as a data science company to exemplify itself as the most reliable platform for data science. The well-prepared data available to try your hands on are the best way to begin your data science journey.

The Bulk of Available Data

 The infinite availability of datasets on Kaggle enables the students to land up in a more productive environment as the opportunity to practice on Kaggle expands. Learning a course is the first step that the students take. But getting them implemented on real-life examples can only be facilitated by Kaggle. Exploring a big bulk of clean data is the floor where Kaggle is regarded as not as efficient as real-life examples but a consistent practice on Kaggle can assure enough experience in an individual. Moreover, notebooks on data exploration are also accessible on Kaggle. Performing data analysis with the help of critical problems being proposed to you makes your data science education even more fulfilling.

Specialized Algorithms to Practice

 Practice algorithms on Kaggle with foundational knowledge in machine learning. Being able to build models and getting them assessed in seconds on Kaggle will enhance the knowledge of algorithms even more. Setting the algorithms also enables you to put forth the innovative ideas that you have envisaged regarding a website or portal. Industries are looking for skilled candidates more than experienced. Practicing on this data science company can constantly present you to the prevailing trends in algorithms and the most sought type. The algorithms on Kaggle also expose you to feature engineering where you come across the practice of identifying, transforming, creating predictive text, and reducing features in the ready-made sets of algorithms.


 A generous number of competitions are hosted on Kaggle. Interestingly, a user can also create competition and that’s what makes this even more exciting. Apart from regular tasks, Kaggle is also the best for attempting assessments. This allows the beginners to grow in steps and reach expertise. Gradual progress in the skills is noticeable in the user. Data science education is not complete without examining the extent of learning.

Free Courses

 Courses on machine learning, coding, feature engineering, python, artificial intelligence, data analysis, data cleaning, data visualization are also available on the website. These courses can build the core concept and foundational knowledge in data science education.

Solve Problems

After gaining a comprehensive understanding of the subjects required to perform data science and having practiced with datasets and algorithms, various data science problems are offered to solve. This is exactly the job that one seeks in the industry. This is primarily what companies hire data science executives for. However, the role of developers is also included but a large number of candidates are hired for solving the issues faced by the company in data science. Classifying, clustering and regression are some of the issues encountered by the companies. Once experience is gained in projects drawing influence from complicated data science problems. Implications become stronger and figuring solutions faster is possible.

Hear from the Experts

Discussion forums are also a part of data science education on Kaggle. Industry experts and data science company operators honor the discussion with their presence. The probable errors and solutions are well-defined by them. Quality issues with data science and improving performance on the data science projects are also discussed efficiently. Listening carefully can result in diminishing the possibility of common mistakes.

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