Christmas Special : Upto 40% OFF! + 2 free courses  - SCHEDULE CALL

- Artificial Intelligence Blogs -

Top 15 Artificial Intelligence Interview Questions and Answers

What was once considered one of the most extraordinary imaginations of various science fiction writers, Artificial Intelligence (AI) is now being slowly infused into our daily lives. This advanced form of technology is taking a prominent shape in terms of practicality and has already started creating a propounding impact in various beguiling ways.

The demand for professionals in the Field of AI is increasing day by day. Whether you are planning to make a career switch to the AI domain or you want to move up your existing AI job profile, the future always looks bright. This also leads to a considerable increase in competition to be placed in a well-defined AI oriented job profile. So, it's mandatory for you to always be prepared ahead of time for all the major AI job interview questions.

We are here to help you out with the most commonly asked questions during an Artificial Intelligence interview. By going through these questions and answers, you can not only have a fair idea about the various questions that you will be asked, but you can showcase your interviewers, your broader knowledge of the applications and implications of AI.

Artificial Intelligence Interview Questions

  1. What is Artificial Intelligence?
  2. List some applications of AI/ what are the various areas where AI (Artificial Intelligence) can be used?
  3. What are the Branches Of AI?
  4. What are the core differences between supervised, unsupervised and reinforcement learning?
  5. Explain types of Artificial Intelligence?
  6. What are the advantages of Fuzzy Logic Systems?
  7. What is an alternate key in AI?
  8. What is the artificial key in AI?
  9. What is compound key in AI?
  10. How Game theory and AI related?
  11. What is FOPL?
  12. What are the components of robotics?
  13. What is simulated annealing Algorithm?
  14. What is Greedy Best First Search Algorithm?
  15. Share your previous project works based on your experience?

Artificial Intelligence Interview Question & Answers

Q1). What is Artificial Intelligence?

AI is an area in the field of computer science, which emphasis on the implication of the human brain's cognitive functions into a machine/system, thereby making it work and act like humans. Some of the activities that can be carried out using computers infused with AI include:

  • Learning and planning
  • Speech recognition
  • Problem-solving

Q2). List some applications of AI/ What are the various areas where AI (Artificial Intelligence) can be used?

AI has a wide scope for implementation and it can be practically applied in fields of extreme diversity such as:

Read: An Ultimate Guide To AI Engineer Resume
  • The linguistic field for Processing natural language
  • Customer support field as Chatbots, Humanoid customer support robots, sentiment analysis bots
  • IT field such as sales prediction, computing, computer software etc.

Q3). What Are the Branches Of AI?

Artificial Intelligence Interview Questions

  • Neural networks: An artificial neuron network (ANN) is an arithmetic model, based on the edifice and functionality of various biological neural networks.
  • Data mining: Artificial intelligence and data mining techniques have been in combination to solve issues related to diagnosis, segmentation, classification and predictions.
  • Statistical AI: This branch of AI basically deals with domain models that disport both uncertainty and complexity in rational structures.
  • Pattern recognition: This primarily rivets on the apprehension of regularities and patterns in data.
  • Fuzzy logic: A type of multi-valued logic, where the truth values of the variables may vary anywhere between 0 and 1.
  • Swarm Intelligence: A biologically-inspired AI model that's based on the behavior of common insects such as bees, ants etc.
  • Genetic algorithm: A systematic combination of adaptive self-learning algorithm that gets its base from the concept of genetics.
  • Expert system: This is implemented in designing systems that is capable of emulating human's decision-making ability.

Q4). Explain the types of Artificial Intelligence.

Artificial intelligence can be classified into two main categories:

  • Strong artificial intelligence: This is basically creating real intelligence in an artificial way using the principle that even machines can be made sentimental. There are two types of strong AI: Human-like and Non-human like.
  • Weak artificial intelligence: These types of AI systems are created only to solve real-life problems and doesn’t deal with the creation of extremely efficient human-like intelligence.

Q5). What are the advantages of Fuzzy Logic Systems?

The Fuzzy logic system has the following key advantages:

  • The leverage to take inaccurate, malformed and clangorous input information.
  • Extremely easy to understandable and effortlessly constructible logics.
  • The flexibility to add and delete the rules as per our convenience in the FLS system.

Q6). What is an alternate key in AI? 

Alternate Key:  All the candidate keys except the primary keys are known as Alternate Keys.

Q7). What is the artificial key in AI?

Artificial Key: Creating a key artificially by assigning a number to individual record, in the absence of a standalone key.

Read: Artificial Intelligence Certification Guide: Salary, Exam Details and Exam Tips

Q8). What is compound key in AI?

Compound Key:  Integration of various elements to generate an exceptional identified, in the absence of any data elements that specifically defines the subsistence within a construct. 

Q9). What is are the core differences between supervised, unsupervised and reinforcement learning?

The difference can be the best explained using the following diagram:

Types------> Supervised Learning Unsupervised Learning Reinforcement Learning
Definition Training set has both predictors and predictions Training set has only predictors in the data set. They can establish state of art results on any task
Algorithm Linear and logistic regression, support vector machine, native Bayes K-means, clustering algorithm, dimensionality reduction algorithm Q-learning, State-action-reward-state-action (SARSA), Deep Q Network (DQN)
Uses Image recognition, Speech, Recognition, Forecasting Pre-Process the data, Pre-train Supervised Learning algorithm. Warehouses, Inventory Management, Delivery Management, Power system financial, system

Q10). How Game theory and AI related? 

Artificial intelligence system makes use of the game theory for the purpose of enhancement as the requirement is always more than one participant. Hence, the relation between game theory and AI can be explained using the following two points:

  • Participant Design: Game theory is used to achieve maximum utility by enhancing a participant's decision
  • Mechanism Design: This is basically a type of Inverse game theory, where games a specifically designed focusing a group of ultra-smart participants.

Q11). What is FOPL? 

FOPL is the abbreviation for First-order Predicate logic, which is a congregation of formal systems, with the statement being divided into two parts: a predicate and a subject. The predicate holds the potential to define or modify the subject's properties. Artificial Intelligence Interview Questions

Q12). What are the components of Robotics?

Artificial Intelligence Interview Questions We would require the following parts in order to construct a robot:

Read: Exploring the Diverse Uses of AI: From Healthcare to Gaming and Beyond
  • Power Supply: Any power source such as batteries, solar power etc.
  • Actuators: These are required for the conversion of energy into movement.
  • Electric motors (AC/DC): used for rotational movement.
  • Pneumatic Air Muscles: used for contracting purposes while air gets sucked in them.
  • Muscle Wires: Used for passing electric current during contraction.
  • Ultrasonic and Piezo Motors: Used for industrial robots.
  • Sensors: Generic sensors that are used for measurement of the surroundings.

Q13). What is simulated annealing Algorithm?

Annealing is basically the process is of heating a metal and then immediately cooling it to make changes to its internal structure. The same principle is applied in computing where a probabilistic technique is put into practical use for the approximation of a given function's global optimum.

Q14). What is Greedy Best First Search Algorithm?

This is the algorithm process where the node closest to the goal will be expanded first. The default explanation of nodes goes by f(n) = h(n). This technique is applied at a later stage, where priority queue will come into the picture.

Q15). Share your previous project works based on your experience? 

Well, the answer to this question varies based on your work experience and projects you have worked on earlier.

Conclusion

These above-mentioned lists contain the general questions that you might encounter in an Artificial intelligence job interview. You can also do in some further research in your area of interest to gain more confidence for the same. But Always ensure to collect enough information about the company before going in for an interview.

We wish you for your next interview with JanBask Training or explore your knowledge base with our AI certification programs and the assistance given by AI mentors. Happy job hunting!

Read: Top AI Tools List in 2024 : Boost Creativity & Efficiency


fbicons FaceBook twitterTwitter lingedinLinkedIn pinterest Pinterest emailEmail

     Logo

    JanBask Training

    A dynamic, highly professional, and a global online training course provider committed to propelling the next generation of technology learners with a whole new way of training experience.


  • fb-15
  • twitter-15
  • linkedin-15

Comments

Trending Courses

Cyber Security Course

Cyber Security

  • Introduction to cybersecurity
  • Cryptography and Secure Communication 
  • Cloud Computing Architectural Framework
  • Security Architectures and Models
Cyber Security Course

Upcoming Class

2 days 21 Dec 2024

QA Course

QA

  • Introduction and Software Testing
  • Software Test Life Cycle
  • Automation Testing and API Testing
  • Selenium framework development using Testing
QA Course

Upcoming Class

1 day 20 Dec 2024

Salesforce Course

Salesforce

  • Salesforce Configuration Introduction
  • Security & Automation Process
  • Sales & Service Cloud
  • Apex Programming, SOQL & SOSL
Salesforce Course

Upcoming Class

0 day 19 Dec 2024

Business Analyst Course

Business Analyst

  • BA & Stakeholders Overview
  • BPMN, Requirement Elicitation
  • BA Tools & Design Documents
  • Enterprise Analysis, Agile & Scrum
Business Analyst Course

Upcoming Class

8 days 27 Dec 2024

MS SQL Server Course

MS SQL Server

  • Introduction & Database Query
  • Programming, Indexes & System Functions
  • SSIS Package Development Procedures
  • SSRS Report Design
MS SQL Server Course

Upcoming Class

8 days 27 Dec 2024

Data Science Course

Data Science

  • Data Science Introduction
  • Hadoop and Spark Overview
  • Python & Intro to R Programming
  • Machine Learning
Data Science Course

Upcoming Class

1 day 20 Dec 2024

DevOps Course

DevOps

  • Intro to DevOps
  • GIT and Maven
  • Jenkins & Ansible
  • Docker and Cloud Computing
DevOps Course

Upcoming Class

2 days 21 Dec 2024

Hadoop Course

Hadoop

  • Architecture, HDFS & MapReduce
  • Unix Shell & Apache Pig Installation
  • HIVE Installation & User-Defined Functions
  • SQOOP & Hbase Installation
Hadoop Course

Upcoming Class

1 day 20 Dec 2024

Python Course

Python

  • Features of Python
  • Python Editors and IDEs
  • Data types and Variables
  • Python File Operation
Python Course

Upcoming Class

2 days 21 Dec 2024

Artificial Intelligence Course

Artificial Intelligence

  • Components of AI
  • Categories of Machine Learning
  • Recurrent Neural Networks
  • Recurrent Neural Networks
Artificial Intelligence Course

Upcoming Class

1 day 20 Dec 2024

Machine Learning Course

Machine Learning

  • Introduction to Machine Learning & Python
  • Machine Learning: Supervised Learning
  • Machine Learning: Unsupervised Learning
Machine Learning Course

Upcoming Class

8 days 27 Dec 2024

 Tableau Course

Tableau

  • Introduction to Tableau Desktop
  • Data Transformation Methods
  • Configuring tableau server
  • Integration with R & Hadoop
 Tableau Course

Upcoming Class

1 day 20 Dec 2024

Search Posts

Reset

Receive Latest Materials and Offers on Artificial Intelligence Course

Interviews