What Are Some of the Questions That You Must Prepare Before Going for a Data Science Interview


After completing your data science course in India, you’re preparing for a job. Whenever you’re applying for a job position in any company, they are going to check if you are eligible to work there. They determine whether you’ve learned enough to be a proper fit for their company by asking questions that require in-depth knowledge. You won’t be getting questions like “what is computer science course”. This naturally can be quite intimidating and you should be prepared. We can help you sift through the most important questions asked in any data science job interview.

Q: What is Sampling and what are the various ways of sampling?

A: This is a very basic question in any data science interview. Sampling is when we choose a selected few people at random who represent a whole data set. This is done when a required data set is so huge that it might become impossible to create an accurate measurement. The results found through this sample set are assumed as the representation of the whole population. The two types of samplings are probability and non-probability sampling. You can define the types of samplings as well.

Q: What is Selection bias?

A: It is a type of error that occurs if participants for any research aren’t selected at random. If the researcher has any role in selecting the participants, then selection bias occurs which might distort a statistical analysis. There are a few types of selection bias including sampling bias, data selection bias, time interval, or attrition.

Q: What is Logistic Regression?

A: A statistical model is the binary classification that, on top of the probability, uses logit functions to procure a 0 and 1 as a result. You can also provide the equation for Log Loss Function which proves your knowledge.

Q: What is the difference between Regression and Classification?

A: The main difference is in the result. A continuous quantity results through regression whereas discrete labels are provided through Classification. This is also a trick question often asked by interviewers so it’s important to mention that there is no clear difference between the two. Here you can provide the properties of both which shows them that you identified their trick.

Q: Natural Language Processing and some real-life examples of it.

A: This question is often asked by high-tech companies. Natural Language Processing deals with converting human language into machine language so that the command can be processed and desired results can be produced. It is a part of artificial intelligence and all smart home devices or voice-controlled applications use National Language Processing.

Q: What are Evaluation Metrics and different types of them?

A: The statistical measure that determines model performance is known as evaluation metrics. The various evaluation metrics used are Confusion Metrics, Accuracy, and Log Loss.

If you’ve attended a proper data science course in India it will not be too difficult to answer these questions. Do remember to go through your study materials to refresh your memory. You are guaranteed to get the job of your dreams.

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