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.
