Program Highlights

  • Dual Specialization Advantage
  • Cloud-Native Engineering Focus
  • AI Enabled Teaching Learning Governance
  • AI-Integrated Application Development
  • AI Applications Courses are Mandatory
  • Apprentice in Final Year Linked to Job
  • Project Based Learning
  • Scope for Higher Education & Entrepreneurship Development
  • Industry-Aligned Curriculum
  • Multi-Cloud & DevOps Exposure
  • Secure Cloud & Cyber Readiness
  • Innovation, Research & Startup Track

Introduction

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.

Tools Covered

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

Program Details

  • B.Tech CSE (Cloud Computing & AI) is a 4-year engineering program that provides a strong foundation in computer science, cloud architecture, AI/ML technologies, and modern software engineering practices.
  • The course enables students to specialize in scalable cloud infrastructure, DevOps, automation, and artificial intelligence while gaining hands-on experience with AWS, Azure, Google Cloud, and key AI frameworks.
  • Regular communication is maintained with parents regarding attendance, academic performance, and internal assessments to support discipline, academic consistency, and student engagement throughout the program.
  • The program includes industry-driven cloud deployments, AI/ML model-building labs, DevOps pipeline exercises, hands-on workshops, and expert-led sessions focused on real-world applications to make students industry-ready.
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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 any recognized JEE or JKUEE & PI or as per AICTE guidelines.

Program Outcome

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.

Course at a Glance

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.

Career Opportunities

  • Cloud Engineer
  • AI Engineer / ML Engineer
  • Data Engineer
  • DevOps Engineer
  • Site Reliability Engineer (SRE)
  • Cloud Security Engineer
  • Full-Stack Cloud Developer
  • Automation Engineer
  • NLP Engineer
  • Deep Learning Specialist

Campus Facilities for Cloud Computing Students

  • Cloud Infrastructure & Virtualization Lab
  • DevOps & Automation Lab
  • Multi-Cloud Learning Lab
  • AI-Integrated Cloud Application Lab
  • Cyber & Cloud Security Lab
  • Research, Innovation & Startup Lab
  • Smart Classrooms & Virtual Learning Ecosystem
  • Placement & Certification Training Centre

Leading Job Sectors

  • Cloud Engineer
  • Cloud Solutions Architect
  • DevOps Engineer
  • Site Reliability Engineer (SRE)
  • Cloud Security Engineer
  • Data Engineer (Cloud-based)
  • Cloud Migration Consultant

Public Sector & Government Organizations

  • DRDO (Defence Research & Development Organisation)
  • ISRO (Indian Space Research Organisation)
  • NIC (National Informatics Centre)
  • BEL (Bharat Electronics Limited)
  • CDAC (Centre for Development of Advanced Computing)
  • BHEL (Bharat Heavy Electricals Limited)
  • NABARD – Data Analytics Division
  • Ministry of Electronics & IT (MeitY)
  • PSUs adopting AI automation (ONGC, NTPC, GAIL)
  • State and Central Government Smart City Projects

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