BSc CS Sem 6 October 2025 October 2025 Data Science Question Paper - Mumbai University | munotes

Questions asked in this paper

• 2) Figures to the right indicate marks

1. Q3 Illustrations, in-depth answers and diagrams will be appreciated
2. Q4 Mixing of sub-questions is not allowed
3. Q1 Attempt ANY FOUR from the following: (20M)
   • (a) Describe various domain specific applications of Data Science
   • (b) Differentiate between Data Science and Artificial Intelligence
   • (c) Explain difficulties in handling unstructured data and explain how difficulties can be resolved
   • (d) What is data cleaning? Discuss the steps involved in handling missing values
   • (e) What is data wrangling? Describe data wrangling techniques = (f) Why Sci-kit Learn is popular among data scientists, explain
4. Q2 Attempt ANY FOUR from the following: (20M)
   • (a) What is EDA? Describe any four data visualization techniques applicable for
   • (b) How hypothesis testing can be done with the help of t-tests and chi-square tests? Give proper examples
   • (c) Justify the comparison between supervised and unsupervised learning
   • (d) Describe stepwise regression with its role in model selection
   • (e) Discuss various techniques available for evaluating model performance
   • (f) Write a note on Artificial Neural Network
5. Q3 Attempt ANY FOUR from the following: (20M)
   • (a) Describe evaluating model for imbalanced data sets
   • (b) What is the role of story telling in data-science, explain
   • (c) Discuss various data management activities used in ensuring data usability
   • (d) Explain data pipeline and the stages involved in ETL
   • (e) Write a note on Seaborn and Tableau visualization tools
   • (f) Describe various data privacy and security considerations in data
6. Q4 Attempt ANY FIVE from the following: (15M)
   • (a) Write advantages of using NumPy Library for data science in Python
   • (b) Define Bias variance tradeoff in terms of Data Science
   • (c) What is AUC? How it can be used?
   • (d) is dummification? Give example
   • (e) Describe application of simple linear regression in predictive modelling
   • (f) Write python program to draw line chart. Assume your own data

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