4 exam sessions, from December 2023 to April 2025. Download one paper, or tick several for a ZIP or one merged PDF. Free, no sign-up.
AIT401 previous year question papers
AIT401 syllabus
Study of this course provides the learners an overview of the concepts and algorithms involved in deep learning. The course covers the basic concepts in neural networks, deep learning, optimization techniques, regularization techniques, convolutional neural networks, recurrent neural networks, autoencoders, generative models. The students will be able to implement deep learning algorithms to solve real-world problems.
Prerequisite: Machine learning concepts
Course outcomes
| CO | Outcome | Level |
|---|---|---|
| CO1 | Illustrate the basic concepts of neural networks, deep learning and its practical issuesApply | Apply |
| CO2 | Outline the standard regularization and optimization techniques for the effective training of deep neural networks.Understand | Understand |
| CO3 | Build convolutional Neural Network (CNN) models for different use cases.Apply | Apply |
| CO4 | Apply the concepts of Recurrent Neural Network (RNN), Long Short Term Memory( LSTM), Gated Recurrent Unit (GRU).Apply | Apply |
| CO5 | Explain the concepts of auto encoder, generative modelsUnderstand | Understand |
Departments that study AIT401
- Artificial Intelligence (S7)
- AI & Data Science (S7)
- Computer Science and Engineering (Artificial Intelligence and Data Science) (S7)
- Computer Science – AI/ML (S7)
- Computer Science and Engineering (Artificial Intelligence) (S7)
- Artificial Intelligence & Machine Learning (S1)
Frequently asked questions
Which KTU scheme is AIT401 in?
Foundations of Deep Learning (AIT401) is in the KTU 2019 scheme and is a PCC course.
How many credits is Foundations of Deep Learning?
Foundations of Deep Learning (AIT401) carries 3 credits.
Which semester is AIT401 taught in?
AIT401 is taught in S1, S7. The semester differs between departments.
Where can I download AIT401 previous year question papers?
This page lists 4 AIT401 question papers. Select them and download as a ZIP or one merged PDF. It is free and needs no sign-up.
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