Future-Focused AI Master’s Program: A 2-year postgraduate degree designed to build advanced software and artificial intelligence professionals for tomorrow’s digital economy.
Industry-Aligned Learning: UGC & NEP aligned curriculum with hands-on AI labs, live projects, internships and certification-based skill training.
High-Growth Career Pathways: Opens opportunities in AI engineering, data science, cloud computing, automation and advanced software development domains.
Innovation-Driven Training: Empowers students to design intelligent systems and digital solutions for healthcare, finance, governance and next-generation IT industries.
Artificial Intelligence & Machine Learning Lab
Data Science & Analytics Lab
Full-Stack Development Lab
Cloud Computing & DevOps Lab
Cyber Security & Network Lab
Database & Big Data Lab
Software Testing & QA Lab
Project & Innovation Lab
Eligibility
Passed any graduation degree Minimum 50% marks (as per university norms) with mathematics or statistics or mathematics related course at 10+2 level is preferred. In case of non-mathematical background, the student must undergo mathematics as bridge course.
Duration
4 Semester (2 Years ) as per NEP guideline
Tuition Fees
₹ 50,000 per Semester
*Fees such as Admission, Caution Money,
Examination, Hostel, and Transport fees are extra.
Selection Criteria
Admission will be done on the basis of merit which includes any recognized JEE or JKUEE & PI or as per AICTE guidelines.
1
Apply advanced computing and AI concepts to real-world problems
2
Design and develop intelligent software and AI-enabled applications
3
Build and deploy machine learning models and data-driven solutions
4
Use cloud platforms and DevOps tools for scalable application deployment
5
Demonstrate professional communication, teamwork and project management skills
6
Follow ethical, secure and responsible AI practices
7
Be prepared for research, higher studies and global certifications
8
Gain readiness for high-growth AI and digital technology careers
Core Subjects: Advanced Programming, Data Structures, DBMS, Operating Systems, Computer Networks, Software Engineering
AI Specialization Areas: Machine Learning, Deep Learning, Data Mining, Natural Language Processing, Artificial Intelligence
Skill Areas: Full-Stack Development, Cloud Computing, DevOps, Data Analytics
Practical Exposure: Advanced labs, mini projects, internships, capstone project
Outcome: AI Engineer, Software Developer, Data Analyst, Cloud Engineer, and higher
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