Data Center Infrastructure for

AI Systems

Understanding how to support AI Hardware in Data Center Facilities

October 16-17, 2025

Only 24 Limited Seats !!!

  • Early Bird Registration: $2100 (August 1 - September 15)

  • General Registration: $2499 (September 16 - October 15)

  • Live-Online Training

  • MST Time Schedule (7:00am - 5:00pm)

Course Overview:
This course provides a comprehensive understanding about key elements to consider when designing, managing, and optimizing data center infrastructure specifically to support Artificial Intelligence (AI) workloads. Participants will explore the unique requirements, challenges, and best practices for AI-centric data centers, focusing on power, cooling, sustainability and safety considerations essential for high-performance AI applications.

Key Learning Objectives:

  • Understand the fundamental differences in data center infrastructure needs for AI systems versus traditional IT workloads.

  • Typical power and cooling solutions to support high-density AI hardware such as GPUs and TPUs.

  • Global Impact of Data Centers, and Clean Power Generation sources that support a sustainable and low emission footprint for AI Data Centers.

  • Best practices for Operations and Maintenance tailored for AI data centers.

  • Manage scalability and redundancy to ensure high availability and fault tolerance in AI environments.

  • Evaluate emerging technologies and sustainability considerations impacting AI data center design.

Course Format:

  • Instructor-led sessions with Data Center expert industry professional

  • Activities based on Scenarios

  • Case studies

  • Open Book Exam (75% passing score)

Certification:
Upon successful completion (training + exam), participants will receive a Certification of Successful Completion, validating their knowledge in Data Center Infrastructure for AI Systems.

NOTE: There is a waiting period of 30 days to retake the exam, without additional cost. A “Certificate of Attendance” is issued to those not passing the exam.

What is Included with the training:

  • Complete Course Deck (PDF Format)

  • Certificate of Successful Completion (75% Pass Mark) or Certificate of Attendance (PDF Format)

  • Digital Credential (Successful Completion)

Who Should Enroll:

  • Data center professionals aiming to specialize in AI system infrastructure

  • IT managers and project leaders overseeing AI data center deployments

  • Engineers and architects designing and optimizing data centers for AI workloads

  • Data Center Consultants

About the Instructor

Jorge A. Gil, DCEP, ATS

With over 30+ years of Professional Experience, Jorge have worked doing Data Center design, and Consulting, and designing/instructing Data Center Training programs.

He is a current Instructor for DOE DCEP program (https://datacenters.lbl.gov/dcep), (for US and International Attendees).

He is the author of Data Center methods and metrics (IT Room Utilization, Downtime Severity Levels, Site Location Risk Index, etc.) exhibited in Global Data Center events and Journals (Open Compute Project, 7x24Exchange International, Disaster Recovery Journal).

Recently, He authored an article proposing a classification / standardization for Rack Densities categories, including Conventional IT Loads and HPC & AI Loads (Fall Issue 2025 - www.7x24exchange.org).

Course Content and Modules:

1.AI Evolution

  • AI Evolution Timeline

  • Near Future of AI Systems

2. AI, ML, DL, Introduction

  • Introduction to AI Processes

  • AI Workloads

    • Training

    • Inference

  • HPC Workloads

3. AI Systems Hardware

  • AI Servers

    • Type of Processors (CPU, GPU, DPU, TPU, NPU)

      • Features

      • Typical Applications

  • AI Storage

  • AI Networking

  • AI Clustering

4. AI Racks Considerations

  • Rack Densities Categories

  • Sizing AI Rack Power

    • Design Rack Density

    • Examples of Rack Elevations (42u, 45u, 48u, etc)

    • Weight Considerations

5. Cooling Technologies and Distributions

  • Fundamentals

    • Cooling Overview

    • Facility Heat Transfer (FWS/CWS)

    • Environmental Conditions

      • CFM, IAT Temp. RH

      • Dust and Particle Control

    • Cooling: Air-based Vs. Liquid-based

      • Rack Densities and Cooling Technologies

      • Efficiency

      • Reliability

  • Air-Based Cooling

    • Airflow Limitations

    • Air Management

      • Containment Strategies

  • Liquid Cooling

    • Liquid Cooling Overview

    • Considerations (Water Quality, etc)

    • Rear Door Heat Exchanger

      • Passive Rear Door HX

      • Active Rear Door HX

    • Immersion Cooling (IC)

      • Single-Phase IC

      • Two-Phase IC

    • Direct-to-Chip (D2C)

      • Single-Phase D2C

      • Two-Phase D2C

    • Other Systems

6. Power Distributions

  • Data Center Power Distribution Overview

    • DC vs AC Power Distributions

  • Other Power / Electrical Considerations

    • Higher Densities and Recovery Time Objectives (RTO)

7. Workshop - Reference Designs

  • Case Studies

8. Sustainability and Energy Efficiency

  • Global Impact of Data Center Industry

  • Controlling Water and Emissions

  • Controlling Energy Efficiency

9. Clean On Site Power Generation

  • Potential Need for Continuous Power Generation (On Site)

  • Clean Energy Sources

    • Hydrogen

    • Biodiesel

    • Nuclear

    • Natural Gas as a “Bridge Fuel”

10. Operation and Management Considerations

  • Operations & Management

  • Safety Considerations

  • Maintainability Considerations

  • Installing and Decommissioning ITE

NOTE: Course content is subject to change without notice.