AI Infrastructure & Platform Engineering

Description

• Course ID:
  • IC-805-E-07
• Content: This course covers the design, architecture, and operation of modern AI platforms in enterprise environments. The focus is on the technical infrastructure required to deploy AI and machine learning systems in a scalable, secure, and efficient way. The course emphasizes architectural principles for AI platforms and their integration into existing IT landscapes.
  • Key Topics:
    • Architecture of modern AI platforms (enterprise AI stack)
    • Cloud, on-premises, and hybrid architectures for AI
    • Containerization of AI applications
    • Workload orchestration using Kubernetes
    • Use of container technologies such as Docker for AI workloads
    • GPU-based infrastructure for training and inference
    • Data pipelines for AI systems (batch and streaming approaches)
    • Storage and data architectures for AI applications
    • Scaling AI systems in production environments
    • Multi-model and multi-service architectures
    • Edge AI and distributed AI systems
    • Integration of AI platforms into enterprise IT environments
    • Security and governance aspects at the infrastructure level
  • Practical Components:
    • Design of an example AI platform architecture
    • Setup of a containerized AI environment (conceptual or demo-based)
    • Simulation of a scalable AI deployment architecture
    • Analysis of cloud vs. on-prem AI strategies
• Prerequisites:
  • Required:
    • IC-805-G-04 – Developing and Integrating AI Systems, or
    • Equivalent experience in software development or IT architecture
  • Recommended:
    • IC-805-G-06 – MLOps & AI Operations (for understanding operational processes)
    • Basic knowledge of cloud or container technologies
    • Not suitable for complete beginners without IT or development background.
• Certification Requirement:
  • Without certification option
• Conduction Method:
  • Online (For on-site or in-house training, please send us a request via our contact form (Contact - intellcert). We will get in touch with you shortly thereafter.)
• Language:
  • English
• Target  Audience:
  • Cloud and platform engineers
  • DevOps and MLOps teams
  • AI architects and solution architects
  • IT infrastructure managers
  • Technical project leads of large AI initiatives
  • Participants of IC-805-G-04 to IC-805-G-06
• Learning Objectives:
  • Participants will be able to:
    • Explain and apply architectural principles of modern AI platforms
    • Evaluate cloud, on-premises, and hybrid AI strategies
    • Containerize and scale AI workloads
    • Define infrastructure requirements for AI systems
    • Classify data and model pipelines within platform architectures
    • Plan GPU and compute resources for AI systems
    • Consider basic security and governance aspects at platform level
    • Design a simple AI platform architecture
• Note:
  • Displayed price excl. VAT