Leveraging Agentic AI in Cloud Computing: Strategy and Tool Optimization

Course details

Are you looking to learn more about the promise of AI agent technology in cloud computing? Join instructor David Linthicum as he covers some current use cases as well as future opportunities for leveraging these powerful new systems and tools. Ideal for cloud architects, DevOps engineers, and cloud developers, this course was designed to help boost your understanding of AI, including AI agents, and the intersection with cloud computing. Explore the core concepts and common tools of agentic AI, with examples drawn from real-world applications. David guides you through the process of creating, deploying, managing, and optimizing successful AI agents. Along the way, get recommendations for strategic approaches, advanced tooling techniques, and practical guidance on evaluating agents for performance, impact, and efficiency. By the end of this course, you’ll be equipped with the skills you need to harness the power of agentic AI to drive innovation and value for your organization.

Learning objectives
Explain the basics of agentic AI and its relationship to cloud computing, including deployment types, use cases, and common tools.
Describe the process of creating and deploying agent-based AI systems, including architecture types, strategic approaches, and tools.
Evaluate the success of an AI agent deployment using core metrics that define business impact.

Concepts

0. Introduction

01 - Introduction to AI agents in cloud computing

1. Introduction to AI Agents in the Cloud

02 - Overview of AI agents in the cloud
03 - Definition and types of AI agents
04 - Use cases for AI agents in the cloud
05 - Case study #1
06 - Case study #2
07 - Challenge - Identifying the use cases for AI agents
08 - Solution - Identifying the uses cases for AI agents

2. Generative AI Tools and Platforms

09 - Overview of generative AI tools
10 - Autonomous task management tools
11 - Decision-making and reasoning tools
12 - Monitoring and incident management tools
13 - Security and compliance tools
14 - Content and media generation tools
15 - Customer interaction and support tools
16 - Challenge - Identifying the right AI agent tools for XYZ Corp
17 - Solution - Identifying the right AI agent tools for XYZ Corp

3. Building AI Agent Solutions in the Cloud

18 - Autonomous resource management
19 - Automated DevOps pipelines
20 - Intelligent monitoring and alerting
21 - Personalized customer experience
22 - Predictive maintenance and issue resolution
23 - Enterprise data integration and AI
24 - Agentic AI for dynamic content generation
25 - Challenge - Building a personalized customer experience agent for XYZ Corp
26 - Solution - Building a personalized customer experience agent for XYZ Corp

4. Integrating AI Agents into DevOps Practices

27 - Enhancing CI CD pipelines with AI
28 - Security and compliance
29 - Testing and deployment

5. AI Agents and Cloud Architecture

30 - AI agents and data integration
31 - AI agents and storage
32 - AI agents and compute
33 - AI agents and containers
34 - AI agents and serverless
35 - Challenge - Creating an agent AI cloud architecture for XYZ Corp
36 - Solution - Creating an agent AI cloud architecture for XYZ Corp

6. AI Workflows and Prompt Engineering

37 - Crafting prompts to guide agentic behavior in AI models
38 - Refining AI prompts based on performance
39 - Challenge - AI workflows and prompt engineering at XYZ Corp
40 - Solution - AI workflows and prompt engineering at XYZ Corp

7. Important Topics for Agent AI

41 - Intelligent monitoring and incident management
42 - Enterprise data integration
43 - Human-AI collaboration in the cloud

8. The Future of AI Agents in the Cloud

44 - Multi-agent systems
45 - AI-driven cloud security
46 - Scalable and resilient architectures
47 - Advanced data integration techniques
48 - Interoperability of AI agents across cloud platforms
49 - AI agentic in edge computing

Conclusion

50 - Learning more about AI agents
51 - Where to get more information