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LevelMaster in Data Science (SMS, TU)
SubjectFundamentals of Data Science
Year2080 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

Is CRISP-DM waterfall or Agile? Support your answer with suitable example.

crisp-dmmethodology
2Short answer3 marks

What are the different commonly used data formats used across data science project?

data-formats
3Short answer3 marks

What do you mean by regression and classification? Are they supervised or unsupervised technique? Justify.

regressionclassificationsupervised-learning
4Short answer3 marks

What do you mean by backpropagation? Conceptually, how do they differ from forward propagation in neural network?

backpropagationneural-networks
5Short answer3 marks

How group unaware selection and adjusted group thresholds are useful for addressing bias?

biasfairness
B

Group B

5 questions·6 marks each
6Long answer6 marks

Explain the different phase of OSEMN lifecycle for data science projects.

OR

What do you mean by TDSP? How does it differ from other frameworks?

osemntdsplifecycle
7Long answer6 marks

Explain time series analytics with its types.

time-series
8Long answer6 marks

What do you mean by missing data? How do you tackle them in any data science project? Explain with example of your own.

missing-datadata-cleaning
9Long answer6 marks

Elaborate the concept behind Naïve Bayes algorithm for classification task.

naive-bayesclassification
10Long answer6 marks

Apply map-reduce to the following set of data:

Data, Science, Engineering
Engineering, Data, Analytics
Analytics, Intelligence, Science

OR

What is Hadoop? Explain the different components of Hadoop.

map-reducehadoop

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How many marks is the Master in Data Science (SMS, TU) Fundamentals of Data Science 2080 paper?
The Master in Data Science (SMS, TU) Fundamentals of Data Science 2080 paper carries 45 full marks and is meant to be completed in 120 minutes, across 10 questions.
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