AI+ Cloud (Self-Paced Training)
Ziele der Schulung
- AI Cloud Infrastructure Management
- Cloud Automation with AI
- Predictive Cloud Analytics
- Cloud Security with AI
- AI-Powered Data Management in Cloud
Zielgruppe Seminar
- 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.
Voraussetzungen
- 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.
Seminarinhalt
Module 1: Fundamentals of Artificial Intelligence (AI) and Cloud
- 1.1 Introduction to AI and Its Application
- 1.2 Overview of Cloud Computing and Its Benefits
- 1.3 Benefits and Challenges of AI-Cloud Integration
Module 2: Introduction to Artificial Intelligence
- 2.1 Basic Concepts and Principles of AI
- 2.2 Machine Learning and Its Applications
- 2.3 Overview of Common AI Algorithms
- 2.4 Introduction to Python Programming for AI
Module 3: Fundamentals of Cloud Computing
- 3.1 Cloud Service Models
- 3.2 Cloud Deployment Models
- 3.3 Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)
Module 4: AI Services in the Cloud
- 4.1 Integration of AI Services in Cloud Platform
- 4.2 Working with Pre-built Machine Learning Models
- 4.3 Introduction to Cloud-based AI tools
Module 5: AI Model Development in the Cloud
- 5.1 Building and Training Machine Learning Models
- 5.2 Model Optimization and Evaluation
- 5.3 Collaborative AI Development in a Cloud Environment
Module 6: Cloud Infrastructure for AI
- 6.1 Setting Up and Configuring Cloud Resources
- 6.2 Scalability and Performance Considerations
- 6.3 Data Storage and Management in the Cloud
Module 7: Deployment and Integration
- 7.1 Strategies for Deploying AI Models in the Cloud
- 7.2 Integration of AI Solutions with Existing Cloud-Based Applications
- 7.3 API Usage and Considerations
Module 8: Future Trends in AI+ Cloud Integration
- 8.1 Introduction to Future Trends
- 8.2 AI Trends Impacting Cloud Integration
Module 9: Capstone Project
- 9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem
Optional Module: AI Agents for Cloud Computing
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- Understanding AI Agents
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- Case Studies
- Hands-On Practice with AI Agents
Hinweise
Prüfung und Zertifizierung
Exam Details
- Duration: 90 minutes
- Passing Score: 70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
Exam Blueprint
- Fundamentals of Artificial Intelligence (AI) and Cloud - 5%
- Introduction to Artificial Intelligence - 7%
- Fundamentals of Cloud Computing - 8%
- AI Services in the Cloud - 10%
- AI Model Development in the Cloud- 15%
- Cloud Infrastructure for AI - 15%
- Deployment and Integration - 15%
- Future Trends in AI + Cloud Integration - 20%
- Capstone - 5%
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Übersicht: AI Certs Schulungen Portfolio
