Master in Data Science (SMS, TU) Fundamentals of Data Science Question Paper 2078 (Set Second Assessment, p3 (typed sheet, titled 'Fundamentals to Data Science')) Nepal
This is the official Master in Data Science (SMS, TU) Fundamentals of Data Science question paper for 2078 Set Second Assessment, p3 (typed sheet, titled 'Fundamentals to Data Science'), as set in the Second Assessment examination. It carries 45 full marks and a time allowance of 120 minutes, across 10 questions. On Kekkei you can attempt this Fundamentals of Data Science past paper online with a timer, get instant AI feedback and step-by-step solutions, and track the topics where you lose marks — completely free. Whether you are revising for your Master in Data Science (SMS, TU) Fundamentals of Data Science exam or solving previous years' question papers, this 2078 paper is a great way to practise under real exam conditions.
| Level | Master in Data Science (SMS, TU) |
|---|---|
| Subject | Fundamentals of Data Science |
| Year | 2078 BS |
| Exam session | Second Assessment · Set Second Assessment, p3 (typed sheet, titled 'Fundamentals to Data Science') |
| Full marks | 45 |
| Time allowed | 120 minutes |
| Questions | 10, all with step-by-step solutions |
Group A
What are the differences between linear regression and logistic regression? Explain with an example.
What kind of problem can a Decision Tree solve? Explain with an example.
Define Support Vector Machines. Describe briefly how SVMs are used for classification.
Define and list out major differences between Data Warehouse and Data Lake.
What is Hadoop? List and briefly discuss the major parts of a Hadoop system.
Group B
Please answer any ONE of the following:
(a) What are the advantages of using a random forest algorithm?
OR
(b) Explain with a real life example where k-NN algorithm can be used to solve problem.
List two main issues with privacy and data ethics with examples.
Explain how Demographics Parity and Equal Opportunity can help address biases.
What is big data? Explain the five Vs of big data.
Please answer any ONE of the following:
(a) Explain what is Naïve Bayes. Describe its common use cases with examples.
OR
(b) Explain Decision Trees. Describe its common use cases with examples.
Frequently asked questions
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- How many marks is the Master in Data Science (SMS, TU) Fundamentals of Data Science 2078 paper?
- The Master in Data Science (SMS, TU) Fundamentals of Data Science 2078 paper carries 45 full marks and is meant to be completed in 120 minutes, across 10 questions.
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