A cloud computing syllabus for B.Tech and M.Tech programs typically covers foundational concepts like virtualization, cloud service models (IaaS, PaaS, SaaS), and deployment models (public, private, hybrid). It also delves into specific areas like cloud infrastructure, storage, security, and programming models. For M.Tech, the curriculum is often more specialized, potentially including advanced topics like cloud-native architectures, big data analytics in the cloud, and AI/ML on the cloud. 

Core Concepts:

• Introduction to Cloud Computing
• Cloud Computing Architectures (Client, Application, Service, Runtime, Storage, Infrastructure)
• Virtualization (Server, Storage, Network)
• Cloud Service Models (IaaS, PaaS, SaaS)
• Cloud Deployment Models (Public, Private, Hybrid, Community)
• Cloud Storage and Data Management
• Cloud Security Fundamentals 

Programming and Development:

• Cloud Programming Models (e.g., MapReduce, Spark)
• Cloud Application Development
• Web Services and APIs
• Big Data Analytics in the Cloud
• AI and ML on the Cloud 

Infrastructure and Management:

Cloud Infrastructure Design and Management, Cloud Networking and Security, Cloud Resource Management, Cloud Migration Strategies, and Monitoring and Performance Optimization. 

Specialized Topics (M.Tech):

Advanced Cloud Security, Cloud-Native Architectures, Serverless Computing, Cloud Robotics, and Cloud Economics and Business Models. 

Specific Cloud Platforms (AWS, Azure, Google Cloud):

• Hands-on experience with one or more major cloud platforms
• Cloud-specific services and features
• Cloud certifications (optional but beneficial)