AI Data Center Cooling: Liquid Cooling & HVAC System Design

“This course contains the use of artificial intelligence.”

Master the Engineering Behind AI Data Center Cooling Systems — From Chip to Atmosphere.

Artificial intelligence is transforming data center infrastructure. High-density GPU racks, increasingly powerful processors, and advanced computing workloads are creating unprecedented thermal management challenges.

Traditional air-cooling strategies alone are often insufficient for high-density AI environments. Modern facilities increasingly rely on direct-to-chip liquid cooling, cold plates, coolant distribution units (CDUs), advanced HVAC systems, and high-efficiency heat rejection technologies.

This comprehensive masterclass provides a practical, engineering-focused understanding of how these systems are designed, sized, integrated, operated, and optimised.

What You Will Learn

Throughout the course, you will explore:

• AI Data Center Thermal Design: Understand server heat loads, rack densities, thermal envelopes, heat transfer fundamentals, and cooling design requirements.

• HVAC and Air Cooling Systems: Design airflow strategies using CRAH units, fan walls, containment, in-row cooling, and rear-door heat exchangers.

• Direct-to-Chip Liquid Cooling: Explore cold plates, rack manifolds, coolant selection, technology cooling systems, and liquid-cooling architectures.

• Coolant Distribution Units: Size CDUs, calculate coolant flow rates, evaluate heat exchanger performance, and select suitable configurations.

• Hydraulic Engineering: Calculate pressure losses, pipe sizing, pump head, pumping power, and system performance.

• Heat Rejection Systems: Understand chillers, dry coolers, adiabatic systems, free cooling, and facility water networks.

• Immersion Cooling: Evaluate single-phase and two-phase immersion technologies, applications, and engineering considerations.

• Cooling Reliability and Resilience: Develop redundancy strategies, controls, monitoring, leak detection, failure analysis, and thermal ride-through solutions.

• Energy Efficiency and Sustainability: Calculate PUE, WUE, annual cooling energy, water consumption, and heat-reuse opportunities.

• Integrated Cooling Design: Coordinate mechanical systems with electrical, structural, IT, and facility infrastructure.

Practical Engineering Calculations and Case Studies

Unlike courses focused primarily on general concepts, this program emphasises engineering calculations and design decisions.

You will follow a fictional AI data center project through a complete cooling design process, including thermal load calculations, airflow sizing, coolant flow, piping hydraulics, pump selection, CDU sizing, heat rejection, redundancy, and performance assessment.

Worked examples explain the formulas, input values, calculation steps, engineering results, and design interpretations.

Comprehensive Learning Resources

The course package includes:

• 45 structured lessons covering the AI data center cooling lifecycle.

• 913 pages of technical lesson materials, supplied across 45 PDF study documents.

• 267 Excel-based calculation tools supporting thermal and hydraulic engineering.

• Worked engineering examples with formulas, units, and design interpretations.

• Scenario-based practice questions with detailed answer reviews.

• An integrated fictional AI data center case study.

• Design checklists, revision materials, and supporting resource guides.

These resources are designed to help you develop a structured understanding of the engineering decisions behind modern cooling infrastructure.

Who Should Enrol?

This masterclass is suitable for mechanical engineers, HVAC engineers, data center designers, building services professionals, design managers, technical project managers, and engineers transitioning into AI and high-density digital infrastructure.

Whether you are entering the data center industry or expanding your knowledge of advanced cooling technologies, this course provides a comprehensive technical learning pathway.

Build your understanding of AI data center cooling — from the chip, through the cooling infrastructure, to the atmosphere.

Important: All calculations are provided for educational purposes and are not construction-ready designs. The course is an independent educational product and is not affiliated with, approved or endorsed by ASHRAE, OCP, Uptime Institute, NVIDIA, or any equipment manufacturer. Fictional project details and figures are used for teaching purposes. The course does not prepare learners for an official certification.