Programs
B.Tech. Artificial Intelligence
and Machine Learning
B.Tech. Artificial Intelligence and Machine Learning
The B.Tech in Artificial Intelligence & Machine Learning at S-VYASA Global City Campus is an interdisciplinary programme designed to cultivate advanced expertise in computational intelligence, intelligent systems, and data-driven technologies. The curriculum integrates core engineering principles with contemporary AI and Machine Learning methodologies, enabling students to develop scalable, intelligent applications for complex real-world environments.
Students gain comprehensive exposure to machine learning algorithms, deep learning, natural language processing, computer vision, neural networks, intelligent analytics, and automation systems. The programme emphasises analytical reasoning, algorithmic problem-solving, and the design of adaptive AI-driven frameworks capable of transforming modern industries.
Through rigorous laboratory training, coding-intensive projects, and industry-oriented learning under the School of Engineering and Technology, students acquire practical proficiency in designing, training, and deploying intelligent systems. With applications spanning healthcare, finance, cybersecurity, robotics, business intelligence, education, and smart technologies, graduates are well-positioned to contribute to the evolving global landscape of Artificial Intelligence and digital innovation.
Eligibility
- Passed the 10+2 (or equivalent) examination from a recognized Board with Physics and Mathematics as compulsory subjects, along with one of the following subjects: Chemistry, Computer Science, Electronics, Information Technology, Informatics Practices, Biology, Biotechnology, Technical Vocational Subject, Engineering Graphics, Business Studies, or Entrepreneurship, as prescribed under the AICTE Approval Process Handbook 2024–2027.
- Candidates must have secured a minimum of 45% aggregate marks (40% for reserved categories) in the qualifying subjects taken together. Candidates who have passed the D.Voc. stream in the same or allied sector are also eligible.
Program Highlights
Comprehensive AI & Computing Curriculum:
A structured blend of computer science, artificial intelligence, machine learning, data science, and intelligent computing technologies.
Machine Learning & Deep Learning Focus:
In-depth training in supervised and unsupervised learning, neural networks, predictive modelling, and deep learning frameworks.
Data Analytics & Intelligent Systems:
Strong emphasis on data processing, pattern recognition, business intelligence, and AI-driven decision-making systems.
Programming & Algorithmic Expertise:
Hands-on training in programming languages, data structures, algorithms, and AI model development.
Natural Language Processing & Computer Vision:
Exposure to advanced technologies involving language understanding, image processing, and intelligent perception systems.
Experiential Learning Ecosystem:
Practical learning through coding labs, AI simulations, hackathons, industry projects, and research-oriented assignments.
Industry-Aligned Pedagogy:
Curriculum aligned with emerging technologies, Industry 4.0 requirements, and real-world AI applications.
Research & Innovation Orientation:
Encourages innovation, interdisciplinary research, and the development of scalable AI-powered solutions.
Future-Ready Skill Development:
Equips students for roles in Artificial Intelligence, Machine Learning, Data Science, and Intelligent Automation domains.
Career Outcome
Robotics Engineering Roles:
Opportunities as Robotics Engineer and Robotics Systems Designer, focusing on autonomous systems, robotic integration, and intelligent machine development.
Automation & Industrial Engineering:
Roles such as Automation Engineer and Industrial Automation Specialist, working on smart manufacturing, process optimisation, and Industry 4.0 ecosystems.
Control Systems Engineering:
Positions as Control Systems Engineer, specialising in feedback mechanisms, PLC programming, and real-time process control.
Embedded Systems & Mechatronics:
Careers as Embedded Systems Developer and Mechatronics Engineer, integrating hardware and software for advanced automation systems.
Advanced Technology Domains:
Opportunities in robotics simulation, autonomous systems, drones, smart factories, and intelligent infrastructure.
Cross-Industry Demand:
Career prospects across manufacturing, automotive, aerospace, logistics, energy, and emerging smart technology sectors.
Research & Higher Education Pathways:
Strong foundation to pursue M.Tech, PhD, or specialised certifications in Robotics, Automation, and Control Engineering.
Entrepreneurial Pathways:
Equips graduates to build innovation-led ventures in robotics, automation, and next-generation industrial solutions.
Begin your journey into the future of intelligent technologies with the B.Tech in Artificial Intelligence & Machine Learning at S-VYASA University. The programme combines strong engineering foundations with hands-on learning to prepare students for impactful careers in AI-driven innovation and emerging technologies.
FAQ's
A B.Tech. in Artificial Intelligence and Machine Learning is a four-year engineering programme that combines computer science, programming, data analysis and intelligent technologies. Students learn to develop systems that can analyse data, recognise patterns, learn from experience and support automated decision-making.
Salary depends on the candidate’s technical skills, projects, experience, job role and employer. Graduates may begin in entry-level AI, machine learning, data analytics or software roles, with higher earning potential as they gain specialised skills and industry experience.
Yes, it can be a valuable choice for students interested in programming, mathematics, data and emerging technologies. The programme can lead to opportunities in artificial intelligence, machine learning, data science, intelligent automation and software development.
Candidates must have passed 10+2 or an equivalent examination with the subjects prescribed by the University. They must obtain at least 45% aggregate marks in the relevant subjects, with a minimum of 40% for candidates belonging to reserved categories. Candidates who have passed D.Voc. in the same or an allied sector may also be eligible.
The number of subjects varies across semesters and according to the approved curriculum. The programme generally includes programming, data structures, algorithms, mathematics, machine learning, deep learning, natural language processing, computer vision, data analytics, laboratories, projects and electives.
Eligible candidates can apply through the official S-VYASA admission portal. Applicants must complete the application form, submit the required documents and follow the admission process prescribed by the University.
The salary package varies according to the recruiter, job role, student performance, technical skills and market conditions. Applicants should contact the S-VYASA admissions or placement team for the latest official programme-specific placement and salary details.
