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コース概要
Introduction to Private AI with Ollama
- Overview of Ollama’s role in enterprise AI
- Benefits of running AI models privately
- Comparison with cloud-based AI solutions
Setting Up a Secure AI Infrastructure
- Deploying Ollama on on-premise and self-hosted servers
- Configuring access controls and authentication
- Implementing encryption for AI model data
Deploying AI Models in a Private Environment
- Loading and managing LLMs locally
- Optimizing performance for private deployments
- Ensuring AI model version control and updates
Building Secure AI Workflows
- Designing AI-driven automation pipelines
- Integrating Ollama with enterprise applications
- Ensuring compliance with security and governance policies
Optimizing AI Model Performance and Efficiency
- Leveraging GPU acceleration for high-speed processing
- Fine-tuning AI models for private workloads
- Monitoring and maintaining AI performance
Ensuring Compliance and Data Privacy
- Best practices for enterprise AI security
- Data retention policies for private AI models
- Regulatory compliance considerations (GDPR, HIPAA, etc.)
Scaling Private AI Workflows
- Expanding AI capabilities in large enterprises
- Hybrid approaches combining private and cloud AI
- Future trends in private AI deployment
Summary and Next Steps
要求
- Experience with AI model deployment and management
- Familiarity with network security and access control
- Understanding of enterprise automation and DevOps practices
Audience
- Enterprise architects designing AI-powered workflows
- Security analysts ensuring compliance and data privacy
- Automation engineers integrating AI into business operations
14 時間
