Data science is an interdisciplinary field that has raw data, analyses, and comes up with patterns that are used for extracting valuable insights. Data science has gained huge importance due to the value of data. This is considered the new fuel of the future. Data scientists gets the exposure to work in diverse domains and also solve real-life practical problems. A successful data scientist can interpret data, perform innovation and even search for creativity for solving problems. Individuals who are interested in becoming data scientists must avail data science courses.
Let us explore some of the most commonly asked data science interview questions which help to aspire and experienced data scientists:
- What do you mean by data science?
Data science is an interdisciplinary field that constitutes different scientific processes, algorithms, tools, and machine learning techniques for working to help find common patterns and collect sensible insights from raw data with the help of statistical analysis.
- What do you understand about linear regression?
This helps in understanding the relationship between dependent and independent variables. Linear regression is supervised learning which helps in finding a linear relationship between two variables. Here one is the predictor or independent variable, and the other is the response if there is one independent variable which is simple linear regression.
- How is data science different from traditional application programming?
Data science has a different approach to building systems that provide value than traditional application development. In this, we used to analyze the input, figure out expected output and write code and also have rules and statements which are needed for transforming the provided input into expected output.
Data science mainly shifts the processes, and here we need access to large volumes of data that contain necessary input and also map the expected outputs. Data science algorithms use mathematical analysis to generate rules for mapping the given input. This procedure is known as training. Here, we use some data which must be set aside before the training phase to test and check the system’s accuracy.
- What is bias in data science?
Bias is an error that occurs in the data science model due to the used algorithm, which is not strong enough to capture the underlying patterns which exist in data. This error occurs when data is very complicated and ends up in building a model which makes simple assumptions.
- Why is R used in data visualization?
R provides the best ecosystem, which is for data analysis and visualization, with more than 12000 packages in open source type. This has huge community support, which means one can easily find the solution for problems such as stack flow. This has better data management and also supports distributed computing by distributing operations between different tasks and also decreases the complexity and execution time.
Conclusion:
The above-mentioned interview questions helped many data scientists to crack the interview. It is difficult to predict the questions which will be asked in the interview. Going over the practice questions and technical questions is extremely helpful when preparing for an interview. Interested professionals must also avail data science and machine learning course in India to get the right updates.
