Master in Data Science (SMS, TU) Fundamentals of Data Science Question Paper 2078 (Set First Assessment 2078, p1) Nepal

Describe the applications and limitations of Data Science.

What is data science lifecycle? Briefly explain two major data science life cycles used by industries.

List and highlight the differences between structured, unstructured, and semi-structured data with examples of each.

Briefly explain the various methods used to handle missing values during data cleanup.

You want to identify global weather patterns that may have been affected by climate change. To do so, you want to use machine learning algorithms to find patterns that would otherwise be imperceptible to a human meteorologist. Discuss what machine learning method (supervised, unsupervised, reinforcement) would you use and why.

Explain CRISP-DM, its advantages, and the steps involved in it.

OR

Explain TDSP lifecycle and the steps involved. Mention at least two main advantages of using TDSP lifecycle.

With an example, explain how you would determine the True Negative and False Negative data from research dataset.

Explain with examples observation bias and funding bias in a research survey.

Describe, at a high-level, the major steps that need to be taken for data cleanup/munging.

Describe and explain with examples the various types of machine learning methods (Supervised, Unsupervised, and Reinforcement).

OR

Explain with examples and highlight the relationship between Artificial Intelligence and Machine Learning.