Skills you must have to become a Data Scientist Does being a data scientist lure you? There’s nothing wrong if it does. “Data Scientist” has been called the sexiest job of 21st century.
Now the question arises – how to become a data scientist? From whatever information one gets from various resources that it requires comprehensive knowledge of numerous fields like software development, data mining, databases, statistics, machine learning and data visualization to become a data scientist. You don’t have to worry too much. I am not of the same opinion. One doesn’t need to learn too much too soon, all you need to start with is to learn how to read data science job descriptions. This allows you to apply for jobs for which you are already skilled …show more content…
Basic Statistics – The basic understanding of statistics is necessary to become a data scientist. There have been cases where professionals wishing to be data scientist have failed to provide the correct definition of small functions like a p – value. One should have a good know how of statistical tests, distributions, maximum likelihood estimators etc. Just think about your first statistics class. This will also help you with machine learning but one of the more important aspects of your statistical knowledge is to have an understanding of when employing a particular technique is valid. Statistics is relevant to all the organizations mostly to data-driven organizations where product is not data-focused and the stakeholders seek your support in making decisions and designing experiments.
3. Machine Learning – If your organization deals with large volumes of data or has a data-driven product then this is scenario where you might want to understand machine learning methods. This would entail learning the machine learning buzzwords like k-nearest neighbours, random forests and ensemble methods. Since most of these techniques can be implemented using R or Python libraries which means that it wouldn’t matter much if your understanding of algorithms is rather less. Here also, what is more important is to understand which technique should be used and
Now the question arises – how to become a data scientist? From whatever information one gets from various resources that it requires comprehensive knowledge of numerous fields like software development, data mining, databases, statistics, machine learning and data visualization to become a data scientist. You don’t have to worry too much. I am not of the same opinion. One doesn’t need to learn too much too soon, all you need to start with is to learn how to read data science job descriptions. This allows you to apply for jobs for which you are already skilled …show more content…
Basic Statistics – The basic understanding of statistics is necessary to become a data scientist. There have been cases where professionals wishing to be data scientist have failed to provide the correct definition of small functions like a p – value. One should have a good know how of statistical tests, distributions, maximum likelihood estimators etc. Just think about your first statistics class. This will also help you with machine learning but one of the more important aspects of your statistical knowledge is to have an understanding of when employing a particular technique is valid. Statistics is relevant to all the organizations mostly to data-driven organizations where product is not data-focused and the stakeholders seek your support in making decisions and designing experiments.
3. Machine Learning – If your organization deals with large volumes of data or has a data-driven product then this is scenario where you might want to understand machine learning methods. This would entail learning the machine learning buzzwords like k-nearest neighbours, random forests and ensemble methods. Since most of these techniques can be implemented using R or Python libraries which means that it wouldn’t matter much if your understanding of algorithms is rather less. Here also, what is more important is to understand which technique should be used and