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If you are considering a career in Artificial Intelligence, you might not find enough resources around you to guide you through the process.

Artificial Intelligence specific careers are not only luxurious but also rare.

Avenues are opening for more sophisticated applications and roles around Artificial Intelligence, but we’re still short of quality candidates for this role, especially in India.

As such, you may find yourself a bit helpless in this situation.

What are Artificial Intelligence focused roles?

Artificial intelligence is modeled on human neurons; exactly like your brain works with the help of those tiny neurons or messenger cells. This neural network for machines is termed as the Artificial Neural Network.

Several organizations and governments have increased their investment in visionary projects and research in this field as they are aware of the benefits and the potential of data science and AI. An artificial intelligence-powered business will not only be the most profitable one but would also have an edge over others.

To help you out with these questions, we have curated a list of 10 questions to test your understanding of concepts.

Here’s our listicle.

Q1. What is Artificial Intelligence?

A1. A field of study that deals with the research and development of computer systems that work on the tasks requiring human intelligence.

The AI-powered machines are able to mirror cognitive functions, such as learning, speech recognition, decision making and problem-solving etc.

Q2. What is the difference between Data Science, Machine Learning & Artificial Intelligence?

A2. Data Science is an interdisciplinary field that uses data to generate insights and put it to use for the benefit of the business.

Machine Learning is a part of artificial intelligence, systems that actually provide a framework to build sophisticated AI components.

Artificial Intelligence deals with building machines that can imitate human behavior and take decisions and perform tasks that would otherwise require human intervention.

Q3. What are the different types of Artificial Intelligence?

A3. Here are different types of Artificial Intelligence:

Strong AI which builds systems with:

– Decision-making ability
– Capacity to learn from past experiences
– Ability to perform the task on its own

Weak AI

– Only good at performing a particular task.
– Image recognition, speech recognition, are some examples

These are the broad classifications of Artificial Intelligence. Beyond this, there is categorization based on functionality.

Q4. What are the different parts of Artificial Intelligence?

A4. The different domains of Artificial Intelligence include:

Machine Learning

It’s the science of getting computers to act by feeding them data so that they can learn a few tricks on their own, without being explicitly programmed to do so.

Neural Networks

They are a set of algorithms and techniques, modeled in accordance with the human brain. Neural Networks are designed to solve complex and advanced machine learning problems.

Robotics

Robotics is a subset of AI, which includes different branches and applications of robots. These Robots are artificial agents acting in a real-world environment. An AI Robot works by manipulating the objects in its surrounding, by perceiving, moving and taking relevant actions.

Q5. What are some areas where Artificial Intelligence can be used?

A5. Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bioinformatics, Humanoid robot, Computer software, Cyber Security etc.

Q6. What is the difference between strong AI and weak AI?

A6. Strong AI believes that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling human intelligence can be incorporated to computers for more usefulness.

Q7. What is Deep Learning?

A7. Deep Learning is a subset of machine learning that makes use of artificial neural network (ANN), having several layers between I/O layers.

It makes use of artificial neural networks (ANN) and convolutional neural networks (CNN) to help the computer think and work like a human brain.

A Deep Learning Neural Network has the following components:

Input Layer

This layer receives all the inputs and forwards them to the hidden layer for analysis.

Hidden Layer

In this layer, various computations are carried out and the result is transferred to the output layer. There can be n number of hidden layers, depending on the problem you’re trying to solve.

Output Layer

This layer is responsible for transferring information from the neural network to the outside world.

Q8. What is an agent in Artificial Intelligence?

A8. Anything which perceives its environment by sensors and acts upon it are known as Agents. Agents can be Robots, Programs, and Humans.

Agents gather information through perception and reaction. They can further be classified into rational and omniscient agents.

Q9. What are Convolutional Neural Networks?

A9. A Convolutional Neural Network (CNN) is a multilayered neural network used to detect specific patterns in data. CNNs have been used in image recognition, powering vision in robots, and for self-driving vehicles.

Applications of Convolutional Neural Networks

– Facial Recognition
– Advertising
– Object Classification and Detection in Photographs
– Analyzing Documents
– Automatic Image Caption Generation

Q10. What are Recurrent Neural Networks?

A10. Recurrent Neural Networks are used to make sense of sequential data. They are a type of artificial neural network designed to recognize patterns in sequences of data such as text.

Applications of Recurrent Neural Network

– Language Modelling and Translation
– Machine Translation
– Speech Recognition
– Generating Image Descriptions
– Video Tagging

These are basic questions to get you started in Artificial Intelligence. Let us know any beginner terms of Artificial Intelligence that you struggle to understand in the comments section and we will help you out.

Author

Content Writer @ INSAID. A machine learning buff who loves to read, write and explain everything AI!

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