Artificial Intelligence & Machine Learning

Introduction

Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. The field of artificial intelligence has been an interdisciplinary endeavor, requiring deep knowledge of both computational and human sciences. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

Advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. Moreover, the growing impact of AI on society demands that graduates are capable and ethical collaborators, able to ensure the safe and effective adoption of new technologies across domains.

The program begins with introductory courses in programming, computer science, mathematics, and statistics that provide a firm technical foundation. From there, learn core AI concepts and techniques including AI & ML Techniques, Virtual Reality, Web Applications using Machine Learning Techniques, Natural Language and Image Processing, Robotic Process Automation, Business Analytics, Speech Processing, Cognitive systems, Biometrics Systems, computer vision, and language understanding. The program includes a variety of advanced AI electives, enabling technical mastery in specific subfields. Also, specific electives are introduced that will focus on the Application of AI in various industry.

Labs and Practicals

  • Data Structures Lab, Algorithms Lab
  • Micro-controller and Embedded Systems Lab
  • AI and Machine Learning Lab
  • Web Applications Lab
  • Natural Language and Image Processing Lab
  • Mobile Application Development & Robotics Lab
  • Internet of Things Lab

Department Advisory Board

Faculty List

Infrastructure

Research Center

Department Forum

Study Materials

Beyond Syllabus

News Letter