AD-404 Data Science - Jun 2026 Question Paper

Under each question, How to answer lists the points an answer should cover, outlined by CampusPrep from the syllabus. Check the details against your textbook.

1. 7 Marks
   aWhat is Structured Data and Unstructured Data. Explain their characteristics, advantages, disadvantages and real-world applications with examples.
   How to answer

   • Define structured data and unstructured data with examples
   • List characteristics of each type
   • Discuss advantages and disadvantages
   • Give real-world applications
   • Summarize comparison in table
2. 7 Marks
   bExplain the Data Science Road Map in detail. Discuss each phase with suitable examples.
   How to answer

   • Define Data Science road map / lifecycle
   • Explain each phase in sequence
   • Give suitable example for each phase
   • Show flow from problem to deployment
   • Mention tools used in phases
3. 7 Marks
   aExplain graphical methods of data representation with suitable examples.
   How to answer

   • Define graphical representation of data
   • Explain bar chart, pie chart, histogram, line graph, scatter plot
   • Give suitable example for each method
   • Mention advantages of visual representation
4. 7 Marks
   bDifferentiate Basic Probability and Conditional Probability with suitable numerical examples.
   How to answer

   • Define basic probability with formula
   • Define conditional probability with formula $P(A|B)$
   • Differentiate on definition, formula and dependence
   • Solve numerical example for each
   • Summarize differences in table
5. 7 Marks
   aExplain the importance of Unstructured Data Analytics in modern organizations with suitable examples.
   How to answer

   • Define unstructured data analytics
   • Explain need in modern organizations
   • Give examples like social media, reviews, video
   • Discuss benefits for decision making
   • Mention tools and challenges
6. 7 Marks
   bExplain different Data Visualization techniques in detail.
   How to answer

   • Define data visualization
   • Explain bar, line, pie, scatter, heatmap, dashboard techniques
   • Discuss use case of each technique
   • Give examples
   • Mention selection criteria
7. 7 Marks
   aDiscuss the importance of Pivot Tables and Charts in business reporting.
   How to answer

   • Define pivot tables and charts
   • Explain features for summarization and aggregation
   • Discuss role in business reporting and decision making
   • Give example of sales/report use case
8. 7 Marks
   bExplain Multiple Hypothesis Testing and Parameter Estimation Methods.
   How to answer

   • Define multiple hypothesis testing and need for correction
   • Explain Bonferroni, FDR methods
   • Define parameter estimation: MLE, MAP
   • Give examples
   • Compare methods and applications
9. 7 Marks
   aWhat are L1 and L2 Regularization? Explain in detail.
   How to answer

   • Define regularization and need to prevent overfitting
   • Explain L1 (Lasso) with $\sum|w|$ penalty and sparsity
   • Explain L2 (Ridge) with $\sum w^2$ penalty
   • Compare L1 vs L2 with formulas
   • Give examples of applications
10. 7 Marks
    bExplain Bayesian Statistics. Compare Bayesian Statistics with Classical Statistics using examples.
    How to answer

    • Define Bayesian statistics and Bayes theorem
    • Explain prior, likelihood, posterior
    • Define classical/frequentist approach
    • Compare with examples
    • List advantages and applications
11. 7 Marks
    aExplain Pandas in Python in detail with example.
    How to answer

    • Define Pandas and its DataFrame/Series structures
    • Explain installation and import
    • Explain data manipulation functions with example
    • Show sample code and output
12. 7 Marks
    bWrite Python programs to generate Pie Chart and Bar Chart.
    How to answer

    • Import matplotlib.pyplot
    • Write code for Pie Chart with labels and data
    • Write code for Bar Chart with labels and data
    • Show plt.show() and output interpretation
13. 7 Marks
    aWhat is Business Intelligence also discuss its types and component.
    How to answer

    • Define Business Intelligence
    • Explain its types
    • Explain its components like DW, OLAP, reporting
    • Give business examples
14. 7 Marks
    bExplain Modern Business Intelligence tools in detail.
    How to answer

    • Define modern BI tools
    • Explain tools like Power BI, Tableau, Qlik
    • Discuss features: dashboards, self-service, cloud
    • Give examples of use cases
15. 7 Marks
    aExplain the role of Next-Generation Data Scientists in detail.
    How to answer

    • Define next-generation data scientist
    • Explain required skills: AI, big data, cloud
    • Discuss role in automation and ethics
    • Give industry examples
16. 7 Marks
    bExplain different Performance Evaluation Metrics used in Machine Learning.
    How to answer

    • Define performance evaluation need
    • Explain accuracy, precision, recall, F1-score
    • Explain RMSE, MAE for regression
    • Give formulas and examples of when to use each