AI Data Center and Critical Infrastructure Design Corporate Training
Learn to design, monitor, and operate AI-ready data centers with instructor-led corporate training.
This instructor-led program gives your team the skills to design critical infrastructure for AI workloads, from power distribution and liquid cooling to high-density networking and DCIM monitoring. Your employees practice with guided labs that mirror real facility decisions, building the capability to plan capacity, harden resilience, and keep AI infrastructure running reliably.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build a resilient AI infrastructure team
The Edstellar AI DATA CENTER Capability Model
Assess infrastructure capability
Skill checks map your team's facility design, power, cooling, and networking baseline.
Standardize design practices
Your team aligns on sizing methods, redundancy targets, and documentation standards for AI facilities.
Practice in guided labs
Hands-on labs build power, cooling, fabric, and monitoring skill on realistic facility scenarios.
Measure design quality
Assessments and capstone reviews score designs against resilience and efficiency criteria.
Scale facility expertise
Playbooks and runbooks help your team repeat reliable designs across sites and growth phases.
Need more than one program?Get a group quote
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Program Overview: What is AI Data Center and Critical Infrastructure Design?
AI Data Center & Critical Infrastructure Design is Edstellar's instructor-led technical program for infrastructure engineers, facility operators, and network teams supporting AI workloads. Participants learn facility architecture, power distribution and cooling design, high-density networking fabrics, DCIM monitoring, and capacity planning. The focus stays on real facilities: sizing systems that keep GPU clusters reliable.
Training is hands-on from the first module. Participants size power and cooling for AI workloads, benchmark interconnect fabrics, and build monitoring dashboards in guided labs grounded in realistic facility scenarios. Instructors coach them through redundancy planning, failover design, and predictive operations, reviewing every exercise with direct feedback. The program closes with a capstone where each team delivers an end-to-end AI data center design with an operations runbook.
AI workloads overwhelm traditional data centers: dense GPU racks draw extreme power, generate intense heat, and demand low-latency fabrics legacy designs never faced. This program teaches teams to engineer power, cooling, and networking for those demands, with resilience built in from the start. Every technique is practiced in labs, so the learning transfers to live facilities.
Teams produce a complete AI data center design, power, cooling, and network sized, runbook written, then defended under questioning. It's the closest thing to commissioning a facility without pouring concrete.
Delivered as an instructor-led program, the training blends concept sessions with hands-on practice in every module. Your team works through facility surveys, power and cooling sizing exercises, fabric benchmarking, monitoring dashboard builds, and capacity models, ending with a capstone design build reviewed by the instructor. Content adapts to your team's facility types and growth plans, so each cohort practices the workflows it owns. By the end, your team can design, monitor, and administer AI-ready critical infrastructure with confidence.
What's Included in this Workshop for Your Enterprise Teams
- 1
Power and cooling design
Size distribution and cooling for high-density AI racks.
- 2
Interconnect fabric labs
Configure and benchmark AI cluster networking.
- 3
DCIM monitoring practice
Build dashboards, thresholds, and alerting.
- 4
Capacity planning exercises
Model growth and plan resilience and recovery.
- 5
Capstone design review
Defend a full facility design with the instructor.
- Instructor-led delivery across virtual, onsite, and hybrid
- Guided labs in every module with instructor coaching
- Capstone facility design build with instructor review
- Design templates, sizing worksheets, and runbook formats
- Post-training support for design questions
- Batch scheduling aligned to your team's calendar
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
- Plan from 2000+ Industry-ready Training Programs
- Hands-On Labs on Live Infrastructure, Led by Industry Experts
AI Data Center and Critical Infrastructure Design Course Topics and Program Outline
A hands-on 24-hour program that takes your team from AI facility fundamentals to a complete data center design. Each module pairs live instruction with guided labs, so your team practices power, cooling, networking, monitoring, and capacity planning on realistic scenarios, then proves it in a capstone design build.
Built by Edstellar with data center infrastructure engineers
Built by engineers who design and operate high-density data centers in production, shaped around your stack and use cases.
Skill checks baseline your team's power, cooling, and network readiness for AI infrastructure work.
Live instruction covers AI facility architecture, power distribution, and cooling design across 3.5 focused hours.
Guided labs build power, cooling, networking, and monitoring skill across 12 hours of supervised practice.
Your team ships a capstone AI facility design in 8.5 hours, reviewed against resilience and efficiency standards.
From power and cooling design to a capstone AI facility build, every technique is practiced in guided labs.
Delivered as
Delivered as a hybrid program of live instruction and guided labs, scheduled around your team's calendar in flexible batches.
Survey your facility baseline and document power, cooling, and space constraints for AI workloads.
learna)AI workload power and thermal profiles
b)Tier standards and facility layout planning
c)Rack, row, and containment design
d)Power chain fundamentals for data centers
e)Network topology overview for AI clusters
Size a power and cooling design for a high-density AI rack row and validate it against redundancy targets.
practicea)High-density power distribution design
b)UPS and generator redundancy planning
c)Direct-to-chip and immersion cooling options
d)Airflow management and containment
e)PUE measurement and efficiency optimization
Configure and benchmark a test fabric, then tune congestion controls for AI training traffic.
practicea)Spine-leaf architecture for AI clusters
b)InfiniBand and high-speed Ethernet fabrics
c)RDMA and collective communication patterns
d)Congestion control and load balancing
e)Fabric validation and throughput benchmarking
Build a monitoring dashboard with thresholds and alerts for power, cooling, and environmental telemetry.
practicea)DCIM platforms and sensor telemetry
b)Environmental and power monitoring setup
c)Anomaly detection for facility systems
d)Predictive maintenance workflows
e)Incident response and escalation runbooks
Model 3-year AI capacity growth and produce a resilience plan with failover and recovery targets.
applya)Capacity modeling for AI growth
b)Failover and redundancy design
c)Disaster recovery planning
d)Change control and compliance basics
Deliver a complete AI data center design package with sizing calculations, runbook, and stakeholder review.
applya)Requirements capture and design constraints
b)Power, cooling, and network sizing
c)Full design document and operations runbook
d)Stakeholder design review and defense
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Practical facility design and operations skills your team uses on real AI infrastructure from day one.
Design power distribution for AI racks
Size feeders, PDUs, and UPS capacity for high-density GPU racks with redundancy targets.
Engineer cooling for dense AI loads
Select air, direct-to-chip, or immersion cooling and validate airflow and thermal performance.
Architect AI interconnect fabrics
Design spine-leaf fabrics with RDMA and tune congestion controls for training workloads.
Deploy DCIM monitoring
Stand up telemetry, thresholds, and alerting for power, cooling, and environmental systems.
Model capacity and growth
Forecast AI infrastructure demand and plan phased capacity with cost awareness.
Harden resilience and recovery
Design failover, redundancy, and disaster recovery for critical AI facility systems.
Deliver full facility designs
Produce sized designs with runbooks and defend them in stakeholder reviews.
Teams that Benefit from this AI Data Center and Critical Infrastructure Design Group Training
This program serves the groups that design, build, and operate data center infrastructure for AI workloads. Content adapts to each cohort's facility types and tooling, so every team practices the workflows it owns, from rack-level sizing to site-level resilience planning.
Keep AI facilities running at peak reliability
For teams that own daily facility operations and need deeper design and troubleshooting skill for AI-density loads.
Workflow friction
- Thermal hotspots under AI load
- Alert fatigue from noisy telemetry
- Gaps between ops and design teams
How the program helps
- Faster fault isolation in dense racks
- Better thermal and power monitoring
- Cleaner incident handoffs
Practice use cases
- DCIM dashboards
- Incident runbooks
- Thermal audits
Design builds that survive AI growth
For engineers who design power, cooling, and space, and need AI-specific sizing and resilience methods.
Workflow friction
- Underestimating AI power draw
- Cooling retrofits after go-live
- Conflicting stakeholder requirements
How the program helps
- Accurate high-density sizing
- Lower PUE through better design
- Fewer late-stage design changes
Practice use cases
- Power sizing
- Cooling selection
- Redundancy planning
Fabrics that keep GPUs fed
For network teams building the interconnect layer that AI training performance depends on.
Workflow friction
- Bursty collective traffic
- Difficult fabric troubleshooting
- Benchmarking without baselines
How the program helps
- Higher fabric throughput
- Lower job completion times
- Predictable congestion behavior
Practice use cases
- Fabric design
- RDMA tuning
- Throughput testing
Operate AI infrastructure with confidence
For IT operations groups taking on AI facility responsibilities alongside their existing estates.
Workflow friction
- Unfamiliar facility systems
- Capacity surprises
- Recovery plans never tested
How the program helps
- Unified monitoring views
- Clearer escalation paths
- Stronger change control
Practice use cases
- Monitoring setup
- Capacity reviews
- Recovery drills
Cohorts train as a cross-functional workforce, with each small group aligned on shared design and operations standards.
Prerequisites: This program benefits infrastructure engineers, facility operators, and network teams most, especially those supporting or planning AI workloads. Familiarity with basic data center concepts helps but is not required; no prior AI experience is needed. Content adapts to each cohort's facilities and tools, so beginners build foundations while experienced teams deepen design and resilience skill.
Data Center Technician to AI Infrastructure Architect
Tracks how infrastructure professionals progress from basic AI facility concepts to advanced end-to-end design across the program's learn, practice, and apply phases.
A program that grows with infrastructure careers, from AI facility fundamentals to confident end-to-end design.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the format that fits your team's facilities and schedule. Every mode includes live instruction and guided labs.
Hybrid Training
Instructor-led sessions mix onsite and virtual delivery with guided labs throughout. Teams design power, cooling, and fabrics with the instructor coaching each exercise. Hybrid keeps scheduling flexible without losing live interaction.
- Live instruction across onsite and virtual sessions
- Guided labs with real facility design scenarios
- Capstone design build with instructor review
- Flexible batch scheduling for shift teams
Onsite Training
The instructor delivers the program at your facility, so exercises can reference your actual power, cooling, and network environment. Onsite delivery keeps the whole cohort together for design reviews and the capstone build.
- Training delivered at your facility
- Exercises mapped to your infrastructure
- Cohort design reviews in person
- Direct access to the instructor all week
Live Virtual Training
Live virtual sessions deliver the full program online with the same guided labs and capstone review. Your team joins from anywhere, practices in shared lab environments, and gets instructor feedback in real time.
- Live online instructor-led sessions
- Shared lab environments for every module
- Real-time coaching and design feedback
- Session recordings for later review
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Learn from industry experts.
Every session is led by a practitioner who has run monitoring for models in production, not a generalist working from slides.
Sudhanshu
Machine Learning Trainer in Bareilly
19+ years of Experience
Deepesh
Generative AI Trainer in Gaziabad
8+ years of Experience
Chandrika
Data Science and Machine Learning Trainer in Mumbai
10+ years of Experience
Surabhi
Deep Learning trainer in Thane
3+ years of Experience
Anudeep
Data Science with Python Trainer in Hyderabad
11+ years of Experience
Udayraj
Deep Learning and Python Trainer in Ahmednagar
7+ years of Experience
Priyadharshini
Machine Learning with Python Trainer in Chennai
4+ years of Experience
Trainers are matched to your stack and delivery window at scheduling. We confirm your assigned trainer, with a full profile, before the program is booked.
Frequently Asked Questions
Share your team size, timelines, and delivery preference, and we will send a detailed per-group quote with batch options.
Yes. A short discovery call aligns the program scope, labs, and capstone with your facility types and goals.
Yes. The full program runs as live virtual training with shared lab environments and real-time instructor coaching.
Yes. Onsite delivery lets exercises reference your actual power, cooling, and network environment.
The program runs 24 hours of instructor-led training, typically delivered across flexible batches.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
AI facility design follows general data centre management and comes before GPU operations. Your team needs to know how a conventional facility runs before planning the power, cooling, and density AI workloads demand, then operates the GPU estate and works to cut its energy use.
Why Choose Edstellar as Your AI Data Center and Critical Infrastructure Design Corporate Training Provider
Edstellar partners with infrastructure teams to build real facility capability, not just awareness. Your team learns from engineers who run production data centers, practices on realistic AI scenarios, and leaves with designs, runbooks, and templates it can use immediately. As a training provider with 5,000+ certified trainers and 2,000+ courses, we deliver consistent quality at global scale.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Program scope, labs, and capstone adapt to your facility types, AI workloads, and growth plans.
Proven Methodology
A learn, practice, and apply arc moves your team from concepts to a reviewed facility design.
Practice-Based Learning
Guided labs in every module build real sizing, fabric, and monitoring skill with instructor coaching.
Expert Trainers
Data center engineers with production facility experience lead every session and design review.
Global Scale
Consistent program delivery across sites and regions, scheduled around your teams and shift patterns.
Measurable Outcomes
Skill checks and a capstone design defense show exactly what your team can now deliver.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
AI Data Center & Critical Infrastructure Design Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request AI Data Center and Critical Infrastructure Design Training for Your Team
Tell us about your team size, facility types, and timelines. We will respond with a tailored program plan, batch options, and a per-group quote.