AI for Cloud Computing Online Live Class by Experts
Our Training/Internship Process
AI for Cloud Computing - Syllabus, Fees & Duration
Introduction to AI and Cloud Computing (1 Hour)
- Fundamentals of cloud computing
- Introduction to Artificial Intelligence and machine learning
- Cloud service models: IaaS, PaaS, and SaaS
- Applications of AI in cloud environments
Cloud Platforms and Services (2 Hours)
- Introduction to AWS, Microsoft Azure, and Google Cloud
- Cloud computing architecture and deployment models
- Virtual machines, cloud storage, and networking
- Introduction to cloud-based AI services
AI Tools and Cloud-Based Machine Learning (2 Hours)
- Introduction to cloud AI tools and services
- Using pre-trained AI models and AI APIs
- Introduction to generative AI in cloud applications
- Using AI assistants for cloud development tasks
- Practical exercise with a cloud-based AI service
AI Application Deployment (2 Hours)
- Preparing an AI-powered application for deployment
- Deploying a simple application on a cloud platform
- Integrating AI APIs into web applications
- Introduction to serverless computing
- Testing and monitoring deployed applications
Cloud Automation, Security, and Optimization (1 Hour)
- Introduction to cloud automation and DevOps
- Cloud security and identity access management
- AI-assisted troubleshooting and monitoring
- Cloud cost optimization and responsible AI usage
Practical Project and Assessment (2 Hours)
- Build a simple AI-powered cloud application
- Integrate a cloud-based AI service or API
- Deploy and test the application
- Configure basic security and monitoring
- Project demonstration and final assessment
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 10 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
Course Highlights
Learners will explore cloud services and AI tools through practical exercises and real-world projects. The course covers cloud computing fundamentals, AI and machine learning in the cloud, cloud platforms, AI model deployment, cloud storage, serverless computing, cloud automation, security, and infrastructure monitoring. The course is suitable for students who have completed 10th, 12th, any degree, BTech, or a master's degree, as well as freshers and IT professionals who want to develop industry-relevant cloud and AI skills. . AI for Cloud Computing in Sur helps students and professionals understand how Artificial Intelligence and cloud technologies work together to build, deploy, and manage intelligent applications. 
