Data science is a multidisciplinary subject where raw data is mined to draw insights and make strategic decisions. Currently, there are ample job opportunities for students pursuing an online MBA in data science. Such skilled individuals are becoming rock stars of global organisations. As per IBM, demand for data scientists will rise by 28 percent by 2020 and more so in the coming future. You can leap on this successful train by enrolling in a data science MBA online. It will help you get a deep understanding of the subject and aid you in getting a job in a global organisation.
Suppose you are an up-and-coming data science professional pursuing an MBA in data science online. In that case, you should be well versed with the basic and advanced data science concepts to impress prospective employers. Employers are looking for data science professionals who are smart, confident, technically sound, and a great fit for them. And to help you with that, we have combined top interview questions that data science graduates should know before appearing for a job interview.
What does the term data science mean?
Data science is a field that uses scientific and statistical methods, tools, systems, and algorithms to extract insights from structured and unstructured raw data. It is used for strategic decision-making with the help of available data and facts.
What are the qualities of a good data scientist in an organisation?
Data scientists should be innovative, enjoy drawing insights from raw data, be well-versed with tools and techniques, be solution-oriented, inquisitive, have an analytical mind, enjoy automating routine tasks, be creative, and solve complex issues, and be good team workers.
Explain some of the sampling techniques?
Data scientists use data sampling techniques to analyse large data sets. In the case of large datasets, it becomes important to gather data samples that represent the whole population. Data sampling can be categorised into the following broad categories:
Probability sampling technique: Stratified sampling, cluster sampling, Simple random sampling
Non-probability sampling technique: Quota sampling, Convenience sampling, Snowball sampling, Self-selection sampling
When is resampling performed?
Resampling means when a data sample is collected again to perform analysis. Resampling is performed in the following cases:
When you collect the original sample inaccurately, it is not representative of the whole population
To improve the accuracy of the data samples
To ensure that model is apt by performing data testing on different datasets and to ensure variations are taken care of
Define feature vectors
Feature vector contains multiple elements of an object. To put it in simple language, it is a numerical list that forms and represents a picture.