(SEM I) THEORY EXAMINATION 2021-22 AI FOR ENGINEERING

This question paper for AI For Engineering (KMC101) is divided into three major sections—A, B, and C, and students must attempt all sections. It covers fundamental and advanced topics related to Artificial Intelligence, Data Processing, NLP, Deep Learning, Image Recognition, Clustering, and AI applications.

SECTION A – Very Short Answer (20 Marks)

This section contains 10 compulsory questions, each carrying 2 marks.
The questions test basic understanding of:

Meaning of Intelligence

Data and its role in AI

Speech Recognition

Definition of an Artificial Neuron

Object Recognition in image processing

Meaning of Pixel

Algorithm & its basic properties

Real-life uses of NLP

Applications of Deep Learning

Repetition of Speech Recognition to test clarity of concept

This section focuses on fundamental AI terms and definitions.

SECTION B – Short Answer Questions (30 Marks)

Students must attempt any three out of the given five questions.
Each question carries 10 marks.

Topics covered include:

Four classifications of AI with examples

Stages of Data Processing

Natural Language Processing (NLP) and applications

Universal Approximation Theorem

Need & use of Image and Face Recognition in AI

This section checks conceptual clarity, explanation ability, and technical understanding.

SECTION C – Long Answer Questions (50 Marks)

Students must attempt one question from each of the five subsections (Q3–Q7).
Each long question carries 10 marks.

Q3:

Computational Intelligence (or)

Classification of Data

Q4:

Natural Language Understanding & Generation

Deep Learning, its applications & history

Q5:

Robotics vs Artificial Intelligence

Emerging AI Technologies

Q6:

Data Clustering + detailed clustering method

Components of a Conversational Agent

Q7:

Generative Adversarial Networks (GANs)

Robots & their characteristics

This section evaluates deep knowledge, analytical skills, and the ability to write structured, descriptive answers.