Syllabus of Artificial Intelligence for NTA and NET Exam
We will be discussing the syllabus of Artificial Intelligence
specifically for NTA and NET exams. However, the syllabus for AI
is mostly the same for college and university level exams as well.
The syllabus for NTA and NET exams is already available on their
website, so you may wonder why this video is beneficial. The
purpose of this video is to help you make a strategy for exam
preparation.
The Importance of Smart Work
When preparing for competitive exams, it's important to do both
hard work and smart work. Top performers and those who have
qualified for exams generally use both. In this video, we will be
discussing the main topics taken directly from the syllabus. We
will also determine the probability of questions based on past
exams to help you make a study plan. You should focus on the
topics with the highest probability and not skip them.
Other Videos
Before this video, we made syllabus videos for DBMS, Networks,
Operating Systems, NTA, NAT, and GATE exams. You can find the
links to these videos in the description.
Approach to Artificial Intelligence
Many students find Artificial Intelligence a very interesting
subject and study it properly on their own. However, some
students only study for exams and purchase the standard book
for AI, which is 'Artificial Intelligence' by Rich and Knight. Indian
authors like Soraj Kaushik also have similar content but in easier
language. It is important to note that some topics need to be
studied in depth for better understanding and knowledge.
Here are some important topics that need to be studied in depth
for AI:
Approach to AI
Heuristic Search
A*
Adversarial Search
, Minimax Algorithm
Alpha-beta Pruning
Constraint Satisfaction Problems
Backtracking
Forward Chaining
Resolution
Predicate Logic
First-order Logic
Inference
Knowledge Representation
Expert Systems
Neural Networks
Deep Learning
Reinforcement Learning
The first topic, Approach to AI, is the most important and is
frequently asked in exams. It covers topics like Heuristic Search
and A*. It is essential to thoroughly understand these topics for
better performance in exams.
What is Artificial Intelligence | Learn AI with
Real Life Examples | Can Machine Think??
Gate Smashers
Introduction to Artificial Intelligence
Welcome to Gate Smashers! Today, we are going to discuss the
basics of artificial intelligence (AI). Instead of giving you textbook
definitions, let me provide examples of AI that you use on a daily
basis. But first, let's take a look at the history of AI.
We will be discussing the syllabus of Artificial Intelligence
specifically for NTA and NET exams. However, the syllabus for AI
is mostly the same for college and university level exams as well.
The syllabus for NTA and NET exams is already available on their
website, so you may wonder why this video is beneficial. The
purpose of this video is to help you make a strategy for exam
preparation.
The Importance of Smart Work
When preparing for competitive exams, it's important to do both
hard work and smart work. Top performers and those who have
qualified for exams generally use both. In this video, we will be
discussing the main topics taken directly from the syllabus. We
will also determine the probability of questions based on past
exams to help you make a study plan. You should focus on the
topics with the highest probability and not skip them.
Other Videos
Before this video, we made syllabus videos for DBMS, Networks,
Operating Systems, NTA, NAT, and GATE exams. You can find the
links to these videos in the description.
Approach to Artificial Intelligence
Many students find Artificial Intelligence a very interesting
subject and study it properly on their own. However, some
students only study for exams and purchase the standard book
for AI, which is 'Artificial Intelligence' by Rich and Knight. Indian
authors like Soraj Kaushik also have similar content but in easier
language. It is important to note that some topics need to be
studied in depth for better understanding and knowledge.
Here are some important topics that need to be studied in depth
for AI:
Approach to AI
Heuristic Search
A*
Adversarial Search
, Minimax Algorithm
Alpha-beta Pruning
Constraint Satisfaction Problems
Backtracking
Forward Chaining
Resolution
Predicate Logic
First-order Logic
Inference
Knowledge Representation
Expert Systems
Neural Networks
Deep Learning
Reinforcement Learning
The first topic, Approach to AI, is the most important and is
frequently asked in exams. It covers topics like Heuristic Search
and A*. It is essential to thoroughly understand these topics for
better performance in exams.
What is Artificial Intelligence | Learn AI with
Real Life Examples | Can Machine Think??
Gate Smashers
Introduction to Artificial Intelligence
Welcome to Gate Smashers! Today, we are going to discuss the
basics of artificial intelligence (AI). Instead of giving you textbook
definitions, let me provide examples of AI that you use on a daily
basis. But first, let's take a look at the history of AI.
