About AIML:

B.E. in Artificial intelligence and Machine Learning (AIML) 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.

The program begins with introductory courses in programming, computer science, mathematics, and statistics that provide a firm technical foundation. From there, students learn core AI concepts and techniques of AI & ML, Virtual Reality, Web Applications, 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.

Key Highlights:

  • Career Essential Soft Skills Program and Placement Assistance (Job Opportunities Portal, Hiring Drives, Resume Building & many more)

  • Dedicated Student Success Mentor & Career Mentor for 360 Degree Support

  • Live Coding Classes & Profile Building Workshops

  • Mentorship Sessions from Industry Experts

  • Case Studies and Assignments

  • Practical Hands-on Projects


Career Options

  • Software Engineer

  • Big Data Architect

  • Business Intelligence Developer

  • Machine Learning Engineer/ Scientist

Core Subjects:

  • Data Structures

  • Design and Analysis of Algorithms

  • Computer Vision

  • Artificial Intelligence

  • Machine Learning

  • Python Programming

  • Deep Learning

  • Neural Network

  • Human-Computer Interaction

  • Natural Language Processing

  • Mobile Application Development 

  • Robotics Automation

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