An interdisciplinary field that uses scientific processes & ML techniques to extract insights & knowledge from raw data, enabling businesses to make data-driven decisions.
Being proficient in data science leads to high-paying career opportunities with strong job prospects, as data-driven decision making becomes increasingly important across industries.
- Tensorflow - BigML - SAS - Knime - Scikit - Pytorch
Python and SQL are enough for data science interviews, but knowledge of R programming language can provide an advantage in some roles.
Don't let poor preparation hold you back! Equip yourself with a range of Data Science questions and answers, from basic to advanced, to boost your interview success.
1. What are Eigenvectors and Eigenvalues? 2. Define the terms KPI, lift, model fitting, robustness, and DOE. 3. What is a random forest? Explain it’s working.
1. How are time series problems different from other regression problems? 2. What is p-value & what does it indicate in the Null Hypothesis? 3. Why do we need selection bias?
Ready to step up your Data science game? Take on our challenging MCQs and level up your skills for your next interview. Don't wait - start the challenge now!
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