• Cloud Professionals: Enhance your cloud management skills by integrating AI to optimize cloud performance, improve resource utilization. 
• Cloud Architects & Engineers: Learn to leverage AI to design scalable cloud infrastructures, automate cloud provisioning, and enhance security. 
• IT Infrastructure Managers: Use AI to optimize cloud deployment, automate system management, and improve cloud security and disaster recovery planning. 
• Business Leaders: Drive innovation in your organization by adopting AI in cloud technologies to enhance scalability, reduce costs, and optimize cloud solutions. 
• Students & Fresh Graduates: Gain a competitive edge in the cloud computing field by mastering AI tools and techniques that are revolutionizing cloud infrastructure. 

• A foundational understanding of key concepts in both artificial intelligence and cloud computing.
• Fundamental understanding of computer science concepts like programming, data structures, and algorithms.
• Familiarity with cloud computing platforms like AWS, Azure, or GCP.
• Basic knowledge of mathematics as it important for machine learning, which is a core component of AI+ Cloud™ program.

Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.

1. 1.1 Introduction to AI and Its Application
2. 1.2 Overview of Cloud Computing and Its Benefits
3. 1.3 Benefits and Challenges of AI-Cloud Integration

1. 2.1 Basic Concepts and Principles of AI
2. 2.2 Machine Learning and Its Applications
3. 2.3 Overview of Common AI Algorithms
4. 2.4 Introduction to Python Programming for AI

1. 3.1 Cloud Service Models
2. 3.2 Cloud Deployment Models
3. 3.3 Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)

1. 4.1 Integration of AI Services in Cloud Platform
2. 4.2 Working with Pre-built Machine Learning Models
3. 4.3 Introduction to Cloud-based AI tools

1. 5.1 Building and Training Machine Learning Models
2. 5.2 Model Optimization and Evaluation
3. 5.3 Collaborative AI Development in a Cloud Environment

1. 6.1 Setting Up and Configuring Cloud Resources
2. 6.2 Scalability and Performance Considerations
3. 6.3 Data Storage and Management in the Cloud

1. 7.1 Strategies for Deploying AI Models in the Cloud
2. 7.2 Integration of AI Solutions with Existing Cloud-Based Applications
3. 7.3 API Usage and Considerations

1. 8.1 Introduction to Future Trends
2. 8.2 AI Trends Impacting Cloud Integration

1. 9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem

1. 1. Understanding AI Agents
2. 2. Case Studies
3. 3. Hands-On Practice with AI Agents