Websites to know in order to become a Data Scientist / Data Analytics

 

1) Kaggle

 Kaggle is an online community and competition platform for data scientists and machine learning practitioners. It hosts a variety of resources for data science, including data sets, competitions, discussion forums, tutorials, and courses. Kaggle was founded in 2010 by Anthony Goldbloom and Ben Hamner, and it has since grown to become the world’s largest data science community.

 

(i) Why use Kaggle?

There are many reasons why you might want to use Kaggle. Here are just a few:

• To learn data science: Kaggle is a great resource for learning about data science. You can browse the library of data sets, competitions, and tutorials to learn about a variety of data science topics. Kaggle also offers a variety of courses on data science, taught by leading experts in the field.
• To improve your data science skills: Kaggle is also a great way to improve your data science skills. You can participate in the competitions to test your skills and learn from other data scientists. You can also check out the discussion forums to learn from other data scientists’ experiences.
• To win prizes: Kaggle competitions offer cash prizes, which can be a great way to earn money while you learn.
• To connect with other data scientists: Kaggle has a thriving community of data scientists from all over the world. You can connect with other data scientists in the discussion forums or by participating in the competitions.
• To get hired: Kaggle is a great way to get your work noticed by potential employers. Many companies use Kaggle competitions to find talented data scientists.

 

(ii) How to use Kaggle

To get started with Kaggle, you will need to create an account. Once you have created an account, you can browse the library of data sets, competitions, discussion forums, tutorials, and courses. To participate in a competition, simply click on the "Enter Competition" button. You will then be able to submit your code and compete against other data scientists.

If you are new to data science, I recommend starting with the tutorials and courses. Once you have a basic understanding of data science, you can start participating in the competitions.

 

(iii) What are the different types of competitions on Kaggle?

Kaggle hosts a variety of competitions, including:

• Classification competitions: In classification competitions, you are given a set of data and asked to predict a categorical outcome. For example, you might be asked to predict whether a customer will churn or not.
• Regression competitions: In regression competitions, you are given a set of data and asked to predict a continuous outcome. For example, you might be asked to predict the price of a house.
• Time series forecasting competitions: In time series forecasting competitions, you are given a set of historical data and asked to predict future values. For example, you might be asked to predict the stock price of a company.
• Natural language processing competitions: In natural language processing competitions, you are given a set of text data and asked to perform a task such as sentiment analysis, machine translation, or question answering.
• Image classification competitions: In image classification competitions, you are given a set of images and asked to classify them into one of a number of categories. For example, you might be asked to classify images of cats and dogs.
• Image segmentation competitions: In image segmentation competitions, you are given a set of images and asked to identify the different objects in each image. For example, you might be asked to identify the pixels that make up a person’s face in an image.
• Object detection competitions: In object detection competitions, you are given a set of images and asked to identify the objects in each image. For example, you might be asked to identify the cars in an image.
• Machine translation competitions: In machine translation competitions, you are given a set of text in one language and asked to translate it into another language. For example, you might be asked to translate a French text into English.
• Question answering competitions: In question answering competitions, you are given a question and asked to generate the most relevant answer.

 

(iv) Tips for success on Kaggle

Here are a few tips for success on Kaggle:

• Start with the basics: If you are new to data science, start with the tutorials and courses. This will give you a basic understanding of the concepts you need to know to succeed on Kaggle.
• Practice makes perfect: The more you practice, the better you will become at data science. So, don't be afraid to enter competitions and try out new techniques.
• Learn from others: There are many experienced data

 

 

 

2) HackerRank

(i) Introduction - HackerRank is a platform for aspiring software developers and data scientists to practice coding problems, compete against other developers, and prepare for job interviews. The platform offers a variety of resources, including practice problems, competitive programming contests, interview preparation, and a company hiring platform.

(ii) Practice Problems - HackerRank has a large library of practice problems that cover a variety of programming topics. These problems are designed to help you learn new concepts, practice your skills, and improve your problem-solving abilities. The problems are ranked by difficulty level, so you can find problems that are appropriate for your skill level.

(iii) Competitive Programming Contests - HackerRank hosts a variety of competitive programming contests. These contests are a great way to test your skills against other developers and see how you stack up against the best in the world. The contests are timed, so you have to work quickly and efficiently to solve the problems.

(iv) Interview Preparation - HackerRank offers a variety of interview preparation resources, including practice problems, mock interviews, and interview tips. These resources can help you prepare for your next software engineering or data science interview. The practice problems are similar to the problems that you might be asked in an interview, and the mock interviews give you a chance to practice your interviewing skills.

(v) Company Hiring Platform - HackerRank also offers a company hiring platform. This platform allows companies to post job openings and evaluate candidates' coding skills. If you are looking for a job, you can sign up for the platform and start applying for jobs.

(vi) Benefits of Using HackerRank -There are a number of benefits to using HackerRank, including:

• Access to a large library of practice problems: HackerRank has a large library of practice problems that cover a variety of programming topics. This is a great resource for learning new concepts and testing your skills.
• Opportunity to compete against other developers: HackerRank hosts a variety of competitive programming contests, in which you can compete against other developers to solve problems in a limited amount of time. This is a great way to test your skills against the best in the world.
• Access to interview preparation resources: HackerRank offers a variety of interview preparation resources, including practice problems, mock interviews, and interview tips. These resources can help you prepare for your next software engineering or data science interview.
• Opportunity to be recruited by companies: HackerRank also offers a company hiring platform, which allows companies to post job openings and evaluate candidates' coding skills. This is a great way to find your next job.

(vii) How to Succeed on HackerRank - 

Here are a few tips for success on HackerRank:

• Start with the basics: If you are new to programming, start with the beginner-level problems. This will help you learn the basic programming concepts.
• Practice regularly: The more you practice, the better you will become at solving coding problems. So, make sure to practice regularly.
• Read the problem carefully: Before you start coding, make sure to read the problem carefully and understand what you need to do.
• Break down the problem into smaller steps: Once you understand the problem, break it down into smaller steps. This will make it easier to solve the problem.
• Use the right data structures and algorithms: There are many different data structures and algorithms that you can use to solve coding problems. Choose the ones that are most appropriate for the problem you are trying to solve.
• Test your code: Once you have written your code, make sure to test it thoroughly. This will help you identify any errors in your code.

(viii) Conclusion - HackerRank is a great resource for software developers and data scientists. It offers a variety of resources that can help you learn, practice, and improve your coding skills. If you are serious about your career in software development or data science, I highly recommend checking out HackerRank.