Conceptual Model of Artificial Intelligence (AI) and Deep Learning (DL) Courses

Stream of Students Name of the course Pre-requisites

For  Non-Engineering

Deep Learning Applications

  • Non-engineering students with a desire to train machine learning based models


Course Learning Outcome:

At the end of the course, students will be able to:

  • understand the fundamentals concepts of Artificial Intelligence, Machine Learning and Deep Learning
  • apply machine learning and deep learning concepts to train pre-trained models for solving current machine learning based problems

Syllabus Framing Committee:

  • Mr. Unnikrishnan A R, Business Development Director (Higher Education and Research) NVIDIA Corporation
  • Dr. Priyanka Sharma, Professor, Nirma University
  • Dr. Amit Sethi, Associate Professor, Indian Institute of Technology, Bombay
  • Dr. Satyadhyan Chickerur, Professor, K L E Technological University
  • Syllabus for Electives/Core/Add on Course of Deep Learning Applications
  • Electives intended for students in the following programmes:
    • Undergraduate Programmes: Non-engineering students
  • Credit:3  
  • Mode: Theory + Laboratory
  • Course Prerequisites:
  • Non-engineering students with a desire to learn machine learning
  • Knowledge of higher school level maths 
  • Course outcome: Get comfortable with data, be able to do basic tasks with data, and pave way for further learning in related domains