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Cisco (GPU Servers//TPU Server)

The Cisco (GPU Servers//TPU Server) course equips data center engineers and AI infrastructure specialists with skills to deploy and manage high-performance AI workloads on Cisco’s UCS X-Series platform, solving the growing challenge of scaling GPU/TPU resources efficiently. With 78% of enterprises now prioritizing AI infrastructure scalability, this training delivers hands-on expertise in Cisco Intersight, GPU orchestration, and RDMA-based networking for low-latency AI fabrics.

Prepare for the Implementing Cisco Data Center AI Infrastructure (300-640 DCAI) exam and earn the Cisco Certified Specialist – Data Center AI Infrastructure certification. Koenig’s official Cisco-authorized courseware and 30-day lab access ensure mastery, accelerating your path to designing future-ready, intelligent data centers.

40 Hours (5 Days)
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Course Overview

The Cisco (GPU Servers//TPU Server) course, officially known as AI Solutions on Cisco Infrastructure Essentials (DCAIE), is designed for IT professionals aiming to deploy and manage AI workloads on Cisco's advanced data center infrastructure. This training prepares learners for the Implementing Cisco Data Center AI Infrastructure (300-640 DCAI) exam, leading to the Cisco Certified Specialist – Data Center AI Infrastructure certification. Targeted at roles such as AI Infrastructure Engineers, Data Center Architects, and Cloud Operations Specialists, the course addresses the growing demand for AI-ready infrastructure, with 78% of enterprise IT leaders prioritizing AI integration in their data centers according to Cisco’s 2024 infrastructure adoption report. It equips participants with foundational knowledge of AI workloads, generative AI models, and the hardware ecosystems powering modern AI deployments.

Students engage with key technologies including NVIDIA HGX and AMD OAM GPU platforms, Cisco UCS X-Series servers, and Cisco Intersight for unified operations. The hands-on lab component is conducted in a Cisco-integrated environment using real-world tools such as Jupyter Notebook and Cisco Intersight Managed Mode, where learners configure GPU-dense server clusters, deploy open-source GPT models for Retrieval-Augmented Generation (RAG), and build lossless, high-throughput converged fabrics. A core project involves setting up a full AI cluster on Cisco UCS C880A M8 servers with NVIDIA HGX B300, optimizing for trillion-parameter LLM training. This practical experience ensures students master AI workload placement, interconnect efficiency, and policy-driven automation using Cisco’s enterprise-grade platforms.

This course serves as a critical stepping stone toward the CCNP Data Center certification, a globally recognized credential that validates expertise in next-generation data center and AI infrastructure. Professionals with this specialization report an average salary increase of 22%, with AI infrastructure roles averaging $145,000 annually in North America. Koenig Solutions enhances learning with Guaranteed-to-Run scheduling, official Cisco courseware, and 1-on-1 mentoring to ensure mastery. Graduates are positioned to lead AI infrastructure modernization, enabling organizations to scale generative AI securely and efficiently on Cisco’s industry-leading platforms.

What You'll Learn

Design Cisco UCS-X architecture for AI workloads, enabling high-performance computing with Cisco GPU-accelerated servers for AI training and inference.
Deploy Cisco GPU-accelerated servers using Cisco Intersight, simplifying management and scaling of infrastructure to reduce provisioning time by 40 percent for AI projects.
Configure Cisco UCS with NVIDIA HGX GPU modules to maximize AI processing power and achieve sub-millisecond latency in Cisco GPU-accelerated server environments.
Implement Cisco UCS-X modular infrastructure for AI-accelerated compute, supporting scalable and flexible AI model training with Cisco GPU-accelerated servers.
Manage Cisco computing systems via cloud-based Intersight, providing real-time control and automation for Cisco GPU-based inference node deployments.
Optimize Cisco AI infrastructure with UCS AI Sizer, ensuring efficient resource allocation and improved AI workload performance with Cisco GPU-accelerated servers.

Skills You'll Gain

GPU Server Deployment NVIDIA HGX Integration AMD OAM MI300 Setup Cisco UCS X-Series NVLink Configuration TPU Server Optimization PCIe GPU Scaling Cisco Intersight Management AI POD Architecture HBM3E Memory Tuning Blackwell Ultra Platform RoCEv2 Networking NVIDIA RTX Pro 6000 Cisco Nexus 9000 GPU Interconnect Design AI Inference Scaling Enterprise AI Security

Prerequisites

Recommended knowledge before taking this course
  • Basic understanding of Cisco UCS C-Series Rack Servers and Cisco UCS X-Series Modular System hardware and firmware management. Practical experience installing NVIDIA GPUs, configuring them, and setting up CUDA environments on Cisco UCS C240 M6 or Cisco UCS X210c M7 servers. Proficiency in Linux system administration, specifically Ubuntu 22.04 LTS, for managing Cisco GPU infrastructure. Knowledge of high-performance computing networking, including VLANs, QoS, and RDMA over Converged Ethernet, used in Cisco UCS GPU-accelerated systems. Familiarity with AI and machine learning workloads and frameworks such as TensorFlow and PyTorch, optimized for Cisco GPU servers. Experience deploying and managing GPU-accelerated infrastructure within data centers using Cisco UCS systems to accelerate AI and HPC tasks. Candidates should hold a CCNA or Cisco Certified DevNet Associate certification to ensure foundational technical competency.
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Certification Exam

Everything you need to know about the Cisco (GPU Servers//TPU Server) certification exam

Exam Details
Exam Name
Cisco (GPU Servers//TPU Server)
Exam Cost
Not applicable
Format
Multiple choice, labs & case studies
Questions
Duration
Passing Score
Validity
Retake Policy
Not applicable
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Course Curriculum

Structured learning with hands-on labs and real-world scenarios

1
Day 1– Master Cisco AI Infrastructure and Reference Architectures
Define AI, ML, and deep learning architectures Analyze generative AI deployment and challenges Apply AI use cases in enterprise networks Master Cisco AI-ML cluster architecture fundamentals Execute Jupyter Notebook for AI/ML workflows Evaluate Cisco Validated Designs (CVDs) for AI Optimize AI workload placement strategies Govern AI policies and security frameworks
2
Day 2– Cisco AI Network Requirements and Design
Resolve network bottlenecks for AI workloads Select optical and copper technologies for AI Design Cisco AI network connectivity models Deploy Layer 2 and Layer 3 protocols Migrate to dedicated Cisco AI infrastructure Master RDMA and RoCE protocol operations Architect high-performance Cisco Nexus 9000 series fabrics Build lossless RoCE networks with QoS
3
Day 3– Congestion Management for AI Data Handling
Configure ECN and PFC congestion mechanisms Use Cisco Nexus Dashboard Insights for monitoring Analyze complex AI/ML traffic flow patterns Prepare data for high-speed AI pipelines Optimize data performance for AI workloads Implement sustainable Cisco AI infrastructure Guide infrastructure decisions for efficiency Monitor congestion in Cisco AI/ML networks
4
Day 4– Cisco AI Hardware and Compute Resources
Leverage AI-enabling hardware performance benefits Master Cisco GPU server requirements Identify compute resources for AI tasks Deploy Cisco UCS C885A M8 GPU servers Evaluate Cisco UCS X-Series scalable compute solutions Configure virtual infrastructure for AI Implement high-speed storage for AI Use software-defined storage in Cisco AI clusters
5
Day 5– Cisco AI Cluster Deployment and Operations
Provision scalable AI cluster infrastructure Deploy open-source GPT models locally Use RAG with locally hosted models Integrate NVIDIA GPUs with Cisco UCS Optimize fabric with Cisco Nexus Dashboard Deploy LLM inferencing production pipelines Secure AI systems with Cisco Intersight and XDR Migrate cloud models to on-premise Cisco

What's Included in Your Training

Every enrollment comes packed with resources to maximise your learning and exam success

Hands-On Lab

Live Lab Sandbox

Real Environment

Practice in a real lab environment with full access to the tools and services covered in the course.

30+ Guided Labs

30+

Step-by-step lab exercises designed to reinforce each module with practical, hands-on tasks.

Lab Manual Included

Full Guide

Comprehensive lab guide with detailed instructions, screenshots, and troubleshooting tips.

Post-Training Access

30 Days

30 days of extended lab access after your training ends so you can continue practicing.

Career Outcomes

88%

of Cisco (GPU Servers//TPU Server) certified professionals report career advancement within 6 months

Salary Impact

+28%

Average salary increase reported after obtaining the Cisco (GPU Servers//TPU Server) certification

Typical Salary Range (Global)
Entry$90,000–$115,000
Mid$115,000–$145,000
Senior$145,000–$180,000

*Source: Glassdoor / LinkedIn 2025

Job Roles

6
  • AI Infrastructure Engineer
  • GPU Systems Architect
  • Senior Kubernetes Platform Engineer - AI/ML
  • AI Operations Technical Leader
  • Machine Learning Infrastructure Engineer
  • DPU Networking and AI Infrastructure Specialist

Companies Hiring

5,000+
Cisco Microsoft Google Amazon Web Services NVIDIA IBM Accenture Deloitte Hewlett Packard Enterprise

and 5,000+ organizations worldwide seeking Cisco (GPU Servers//TPU Server) certified professionals

Real Transformations

Course Student Reviews

Real results from IT professionals who trained with Koenig — rated 4.9/5 from 18,400+ verified reviews.

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  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

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    Head of L&D, UK Enterprise

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  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified

Frequently Asked Questions

Everything you need to know about the Cisco (GPU Servers//TPU Server) training course

Is a certification exam included in the Cisco UCS AI/ML Infrastructure training, and what is the exam fee if separate?
The Cisco UCS AI/ML Infrastructure training is a vendor-specific specialization on Cisco hardware and does not include a certification exam. While this course supports skills relevant to Cisco Data Center certifications, any associated professional-level exams must be purchased separately through Pearson VUE or Cisco's official portal, typically costing $400.
What training formats does Koenig offer for the Cisco UCS AI/ML Infrastructure course, and is Guaranteed-to-Run scheduling available?
Koenig offers live online instructor-led, classroom-based, and 1-on-1 training formats for the Cisco UCS AI/ML Infrastructure course. All sessions are Guaranteed-to-Run, ensuring no last-minute cancellations. Flexible scheduling includes weekend and evening options, with support for Cisco Learning Credits (CLCs) for authorized enrollment.
How long is lab access provided for the Cisco UCS AI/ML Infrastructure course, and what type of lab environment is used?
Lab access for the Cisco UCS AI/ML Infrastructure course is provided for 30 days post-training via Koenig's cloud-based lab environment. The labs use real Cisco UCS servers integrated with NVIDIA GPUs, offering hands-on experience with PCIe GPU configurations, Cisco Intersight management, and AI workload deployment in a secure sandbox.
What is Koenig's rescheduling and cancellation policy for the Cisco UCS AI/ML Infrastructure course?
Koenig allows free rescheduling of the Cisco UCS AI/ML Infrastructure course with at least 7 days' notice. Cancellations made 7 or more days prior receive a full refund; requests within 7 days incur a 15% administrative fee. The Happiness Guarantee ensures satisfaction or a full refund if training objectives are not met.
What is the exam format and difficulty level for Cisco certifications related to AI/ML infrastructure, including number of questions, types, duration, and passing score?
Cisco professional-level exams typically include 90–110 questions over 120 minutes, with a passing score of 825/1000. Question types include multiple-choice, drag-and-drop, and simulation-based labs focused on data center infrastructure, UCS server configuration, and automation using Cisco Intersight and Nexus Dashboard.
How long is a Cisco certification valid, and what is the renewal process and cost?
Cisco certifications are valid for three years. Renewal can be achieved by passing a current exam, earning Continuing Education (CE) credits (80 for Professional level), or advancing to a higher certification. There is no renewal fee if done before expiration, but retaking an exam costs approximately $400 if expired.
What post-training support does Koenig provide after completing the Cisco UCS AI/ML Infrastructure course?
Koenig provides 30 days of post-training support, including access to mentors, exam preparation guidance, and community forums. Learners also receive lab retake options, resume-building assistance, and updates on Cisco AI POD deployments, UCS server configurations, and certification exam changes to ensure career readiness.
What are the prerequisites or recommended experience for enrolling in the Cisco UCS AI/ML Infrastructure course?
Recommended prerequisites for the Cisco UCS AI/ML Infrastructure course include CCNA or equivalent networking knowledge, familiarity with server hardware, and experience with data center technologies. Prior exposure to AI workloads, GPU acceleration, or Cisco UCS platforms enhances understanding of advanced topics like FlexPod AI PODs and NVIDIA integration.
What career impact and salary increase can be expected after completing the Cisco UCS AI/ML Infrastructure training?
Professionals completing the Cisco UCS AI/ML Infrastructure training can expect roles such as AI Infrastructure Engineer or Data Center Specialist, with average salaries ranging from $95,000 to $130,000. Experts in AI and GPU-accelerated computing on Cisco platforms report faster advancement in cloud and AI-driven organizations.
How does Koenig's Cisco UCS AI/ML Infrastructure training compare to self-study in terms of skill development?
Koenig's Cisco UCS AI/ML Infrastructure training offers structured learning with certified instructors, hands-on labs on real UCS GPU servers, and a curriculum focused on practical deployment. In contrast, self-study lacks practical access to Cisco AI PODs and expert mentorship, which are critical for mastering complex hardware configurations.
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