DTE Code: 3460
DTE Code: 3460

Artificial Intelligence and Machine Learning Engineering

Artificial Intelligence presents a solid foundation in the principles and technologies that underlie many facets of AI, including logic, knowledge representation, probabilistic models, and machine learning. It teaches you to

  • Examine logic and reasoning methods from a computational perspective
  • Learn about agent, search, probabilistic models, perception and cognition, and machine learning
  • Learn about state of the art technologies like Deep learning, Human Computer Interaction and Augmented Reality.
Duration of Program: 4 years (8 Semesters)
Seats:120

Area of study in AIML

  • Data Modeling Predictive Analytics
  • Data Mining
  • Master Data Management
  • OLAP Models
  • Data Warehousing
  • Programming
  • Machine Learning
  • Data Visualization
  • Deep Learning
  • Human Computer Interaction
  • Augmented Reality
  • Software Engineering
  • Linear Algebra
  • Cognitive science theory

Job profiles in AIML

  • Business Intelligence Developer
  • Computer Vision Engineers
  • Research Scientists
  • Machine Learning Engineers
  • Algorithm Specialist
  • Data Scientists

 Prominent industries that apply AIML

  • Cyber Security
  • Manufacturing
  • Healthcare
  • Education
  • Supply Chain Management
  • Fashion
  • Construction
  • Cloud Hosting

Why join UG program in AIML?

Human and machine! Not versus. Deep integration for the purpose of augmenting humanity’s existence. The greatest benefit of Machine learning may be not what the machines learn but what we learn by teaching them.

Come get along with us on this incredible journey of new autonomous future with AIML and be willing to challenge assumptions.

Vision

To be a department focused on quality education and research in Artificial Intelligence & Machine Learning that prepares early professionals contributing to serve the society.

Mission

To provide an academic environment for the development of professionals in the field of Artificial Intelligence and Machine Learning.

To cultivate research culture resulting in knowledge and development of the society.

To enhance academic collaborations for better exposure.

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