15 Most Common Data Science Interview Questions

Data Science is a comparatively new concept in the tech world, and it could be overwhelming for professionals to seek career and interview advice while applying for jobs in this domain. Also, there is a need to acure a vast range before setting out to prepare for data science interview. Interviewers seek practical knowledge on the data science basics and its industry-applications along with a good knowledge of tools and processes. Here is a list of 15 most common data science interview questions that might be asked during a job interview. Read along.

1. Explain Alpha-beta pruning.
A search algorithm that tries to reduce the number of nodes that are searched by the minimax algorithm in the search tree. It can be applied to ‘n’ depth, prunes entire subtrees and leaves.

2. What is Artificial Intelligence?
Artificial Intelligence is a field of computer science wherein the cognitive functions of human brain is studied and tried to be replicated on a machine/system. Artificial Intelligence is today widely used for various applications like computer vision, speech recognition, decision-making, perception, reasoning, cognitive capabilities and so on.
3. List some applications of AI.
Natural language processing
Chat bots
Sentiment analysis
Sales Prediction
Self-driving cars
Facial expression recognition
Image tagging
4. List the programming languages in AI.
5. What is Tower of Hanoi?
Tower of Hanoi is a mathematical puzzle which shows how recursion might be utilized as a device in building up an algorithm to take care of a specific problem. Using decision tree and Breath first search algorithm(BFS) we can solve Tower of Hanoi using AI.
6. What is Turing test?
The Turing test is a method to test the machine’s ability to match the human level intelligence. A machine is used to challenge the human intelligence that when it passes the test, it is considered as intelligent. Yet a machine could be viewed as intelligent without sufficiently knowing about people to mimic a human.
7. What is an expert system & characteristics of expert system?
An artificial intelligence program that has expert-level knowledge about a specific area and knows how to utilize its information to react appropriately. These systems have expertise to substitute a human expert. Their characteristics include –
High performance
Adequate response time
8. List the advantages of Expert system.
Multiple expertise
Ability to reason
Fast response
Unbiased in nature
9. What is A* algorithm search method?
A* is a computer algorithm that is extensively used for the purpose of finding the path or traversing a graph in order to find the most optimal route between the various points called as the nodes.
10. What is Breadth-First Search Algorithm?
Start with the root node, then proceed through neighboring nodes. Further, moves towards the next level of nodes. Till the arrangement is found, produces one tree at any given moment. As this pursuit can be executed utilizing FIFO(First in First Out) data structure. This strategy gives the shortest path to the solution.
11. What is Depth-First Search Algorithm?
Depth-first search is based on LIFO (Last In First Out). A recursion is implemented with a LIFO stack data structure. Thus, the nodes were in a different order than in BFS. The path is stored in each iteration from root to leaf node is linear with space requirement.
12. What is Bidirectional Search Algorithm?
The search begins forward from the beginning state and in reverse from the objective state. The search meets to identify a common state. The initial state way is linked with the objective state in a reverse way. Each search is done just up to half of the aggregate way.
13. What is Iterative Deepening Depth-First Search Algorithm?
The repetitive search process of level 1, level 2 happens in this search. The search process continues till the solution is found. Nodes are generated till a single node is created. Stack of nodes are saved. The search ends once the solution is found.
14. What is Uniform Cost Search Algorithm?
The uniform cost search performs sorting in increasing cost of the path to a node. It expands the least cost node. It is identical to BFS if each iteration has same cost. It investigates ways in the expanding order of cost.
15. How Game theory and AI related?
AI system uses game theory for enhancement, it requires more than one participant which narrows the field quite a bit. The two fundamental roles:
Participant Design: Game theory is used to enhance the decision of a participant to get maximum utility.
Mechanism Design: Inverse game theory, designs a game for a group of intelligent participants. Ex. Auctions.

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