DATA SCIENCE (AD-404) - Important Questions

Explain the differences between structured and unstructured data with suitable examples.

Explain what Data Wrangling is and its importance in data science.

Explain graphical methods of data representation such as pie chart, bar graph and histogram with examples.

Explain the concept of conditional probability with a suitable numerical example.

Explain the importance of unstructured data and unstructured data analytics in modern organizations with suitable examples and uses in domains such as healthcare, finance and social media.

Explain data validation techniques in Excel and their role in improving data accuracy and reducing errors.

Discuss the importance of Pivot Tables and Charts in business reporting.

Explain the concept of logistic regression for binary classification.

Explain Multiple Hypothesis Testing and Parameter Estimation Methods.

What are L1 and L2 Regularization? Explain in detail.

Explain Pandas in Python in detail with example.

Write Python programs using matplotlib/seaborn to generate Pie Chart, Bar Chart, Histogram and Scatterplot.

Explain different Performance Evaluation Metrics used in Machine Learning.

Explain modern Business Intelligence tools in detail with their features and applications.

Explain the role of next-generation data scientists.

What is Business Intelligence, its types and components?