Duration: 4 Years
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USP: 100% Job Opportunity
AICTE & NEP-aligned 4-year engineering curriculum
Hands-on training in AWS, Azure, Google Cloud
Strong foundation in AI, ML, Deep Learning & Data Engineering
DevOps, containerisation, microservices & automation
Cloud-native development & serverless computing
AI-driven application development
Advanced labs: Cloud Lab, AI/ML Lab, DevOps Lab
Industry certifications (AWS, Azure, Google Cloud, Python, ML)
Industry projects, internships & hackathons
Placement readiness training & expert workshops
B.Tech CSE (Cloud Computing & AI) is a NEP-aligned 4-year engineering programme that combines core computer science with advanced cloud technologies and artificial intelligence.
The programme develops strong technical foundations in computing, programming, cloud architecture, machine learning, DevOps, and automation.
Students learn to design, deploy, and manage scalable cloud systems while building intelligent AI-powered applications for real-world industries.
The curriculum integrates hands-on labs, cloud deployments, ML model building, container technologies, and industry-oriented projects for practical learning.
Graduates become industry-ready cloud engineers, AI developers, DevOps professionals, and automation specialists equipped for high-growth technology roles.
Cloud Platform and Tools:
AWS, Azure, Google Cloud
AI/ML Tools:
Python, TensorFlow, PyTorch, Scikit-learn
Automation & Microservices Tools:
Django, Flask, FastAPI
DevOps Tools:
Docker, Kubernetes, Jenkins, Git, Terraform
Programming Tools:
Python, Java, C++, SQL, Shell Scripting
Analytics Tools:
Power BI, Jupyter, Hadoop Ecosystem
Eligibility
Passed 10+2 examination with Physics/Mathematics/ Chemistry/ Computer Science/Electronics/ Information Technology/ Biology/Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/ Entrepreneurship Obtained at least 45% marks (40% marks in case of candidates belonging to reserved category) in the above subjects taken together.Whereas Physics & Mathematics are mandatory courses at 10+2 Level.
OR
Passed D.Voc. Stream in the same or allied sector.(The Universities will offer suitable bridge courses such as Mathematics, Physics, Engineering drawing, etc., for the students coming from diverse backgrounds to prepare Level playing field and desired learning outcomes of the Program. Whereas Physics & Mathematics are mandatory courses at 10+2 Level.
Duration
4 Years (8 Semesters)
Tuition Fees
₹ 75,000 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 entrance, screening & PI.
01
Mastering Cloud & AI Concepts
Develop deep knowledge of cloud architecture, virtualization, AI models, ML algorithms, and scalable computing practices for real-world solutions.
02
Building Technical & Analytical Skills
Gain expertise in AWS, Azure, GCP, Docker, Kubernetes, Jenkins, CI/CD, Python, TensorFlow, and automation tools used in IT ecosystems.
03
Ethical & Secure Computing Practices
Understand cloud security, AI ethics, identity management, compliance, data protection, and responsible use of intelligent technologies.
04
Encouraging Leadership & Innovation
Strengthen problem-solving, team management, and innovation skills needed to lead projects and drive impactful technical solutions.
05
Developing Entrepreneurial Acumen
Learn how AI and cloud technologies enable digital transformation, new product creation, automation, and efficient business operations.
06
Serving Society Through Technology
Apply cloud and AI knowledge to build inclusive, scalable, and intelligent solutions that address societal, economic, and environmental challenges.
Core Subjects: Computer Science Engineering, DSA, Operating Systems, DBMS, Computer Networks, OOP, Software Engineering, Algorithms.
Specialized Areas (AI Minor): Cloud Architecture (AWS, Azure, GCP), Virtualization, DevOps (Docker, Kubernetes, CI/CD), Machine Learning, Deep Learning, NLP, AI Automation, Serverless Computing.
Skill Training: Cloud Deployments, DevOps Pipelines, ML Model Building, Containerization, Git & GitHub, Microservices, API Engineering, Cloud Security, Industry Projects & Internships.
Outcome: Industry-ready Cloud Engineers, AI/ML Engineers, DevOps Engineers, Automation Engineers, and Full-Stack Cloud Developers with strong hands-on experience.
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