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LevelMaster in Data Science (SMS, TU)
SubjectFundamentals of Data Science
Year2079 BS
Exam sessionBoard
Full marks45
Time allowed120 minutes
Questions10, all with step-by-step solutions
A

Group A

5 questions·3 marks each
1Short answer3 marks

List and explain in short three main limitations of Data Science.

data-sciencelimitations
2Short answer3 marks

List three main differences between TDSP lifecycle and OSEMN framework.

tdsposemn
3Short answer3 marks

List the differences between supervised and unsupervised machine learning methods including examples.

supervised-learningunsupervised-learning
4Short answer3 marks

Define and briefly describe neural networks. List a few example use-cases where neural networks can be used.

neural-networksuse-cases
5Short answer3 marks

What are decision trees? What does impurity of a node mean in context of decision tree?

decision-treesimpurity
B

Group B

5 questions·6 marks each
6Long answer6 marks

Explain CRISP-DM in detail with a diagram and an example.

OR

What are the benefits of using OSEMN framework over CRISP-DM? In what scenarios will you use OSEMN instead of CRISP-DM?

crisp-dmosemn
7Long answer6 marks

Define with an example the K-means along with its limitations.

k-meansclustering
8Long answer6 marks

List major differences between linear and logistics regressions with examples.

linear-regressionlogistic-regression
9Long answer6 marks

Explain map-reduce programming paradigm. Include details on how it applies to Hadoop ecosystem.

map-reducehadoop
10Long answer6 marks

Describe in detail how the quality of data can be assessed during data munging.

OR

List and describe how you would address various kinds of issues during data cleanup while doing data munging.

data-mungingdata-quality

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How many marks is the Master in Data Science (SMS, TU) Fundamentals of Data Science 2079 paper?
The Master in Data Science (SMS, TU) Fundamentals of Data Science 2079 paper carries 45 full marks and is meant to be completed in 120 minutes, across 10 questions.
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