Data Center

Cisco Data Center AI Infrastructure (300-640 DCAI)

The data center's newest workload is a GPU cluster, and it will not tolerate a lossy network. Design, build, monitor and troubleshoot the infrastructure underneath AI. Cisco Data Center AI Infrastructure (300-640 DCAI) at RST Forum is a 100-hour instructor-led course (lectures plus hands-on lab practice) at advanced level. Classroom batches run at our Mumbai campus and the same batch streams live-online across India; the fee is ₹30,000.

This course will qualify you for the Cisco Certified Specialist - Data Center AI Infrastructure certification (exam 300-640 DCAI).

Duration
100 hours

Live, Instructor led (ILT)

Training mode
Classroom & online

Mumbai campus

Course fees
₹30,000
Level
Advanced

for working engineers

Certification
300-640 DCAIShow the full certification name

Cisco Certified Specialist - Data Center AI Infrastructure

Exam fees not included.

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Please note that the course fees exclude the certification cost.

Overview

Who should attend

This 100hrs (Lectures + hands-on Lab) Cisco Data Center AI Infrastructure training is designed for network designers, administrators and engineers, storage and server administrators, data center and consulting systems engineers, technical solutions architects and field engineers who are being asked to build and run the infrastructure underneath AI workloads. Candidates will learn to design an AI infrastructure across network, compute, storage and orchestration; to build the lossless Ethernet fabric that RoCEv2 traffic needs, using QoS, PFC and ECN; to configure Cisco UCS compute and storage for GPU workloads; to deploy AI-ready fabrics with Nexus Dashboard, APIC, Hyperfabric and Intersight; and to benchmark, monitor and troubleshoot the result. Candidates will also work with AI itself - JupyterLab, pre-trained models, and a retrieval-augmented generation pipeline built on an open-source GPT model. This is a lab-intensive course and objectives are accomplished through hands on learning.

Outcomes

Skills you'll gain

  • AI infrastructure design
  • Lossless Ethernet: RoCEv2, PFC and ECN
  • GPU compute and Cisco UCS
  • Nexus Dashboard and Intersight
  • Setting up an AI cluster
  • RAG with open-source GPT models

Objectives

What you'll be able to do

The course objectives, as the vendor's own blueprint states them.

  • Explain traditional AI, machine learning and deep learning, and where each one is the right tool.
  • Describe generative AI, the challenges it still has and where the technology is going.
  • Describe how AI supports network management and security through automation, predictive analytics and anomaly detection.
  • Describe AI and ML cluster architecture, and acquire, fine-tune and optimize a pre-trained model.
  • Use JupyterLab and generative AI to write Python and automate network operations.
  • Design AI infrastructure: the components, workload placement and interoperability, governance and compliance, sustainability, and cost-efficient choices.
  • Explain the network challenges AI and ML workloads create, and the connectivity models, media and designs that answer them.
  • Explain how RDMA and RoCE work, and build a lossless RoCE fabric with QoS, ECN and PFC.
  • Configure Cisco UCS compute and storage for AI workloads, and prepare data for AI.
  • Configure an AI-optimized fabric with Nexus Dashboard Fabric Controller.
  • Monitor AI and ML traffic flows and congestion with Nexus Dashboard Insights, and troubleshoot an AI and ML fabric.

Included

What you get

  • Curriculum based on course outlines defined by Cisco Systems.
  • This Instructor-led classroom course is designed with an aim to build theoretical knowledge supplemented by ample hands-on lab exercises.
  • Facility of Lab on cloud available.
  • Courseware includes reference material to maximize learning.
  • Assignments and tests to ensure concept absorption.
  • Repeating of lectures allowed (On approval basis)
  • Candidates can attend lectures online.

Credential

Certification details

Cisco Certified Specialist - Data Center AI Infrastructure300-640 DCAI

After the course

Placements & outcomes

Placement assistance is included: CV preparation, interview drills with real scenario questions, and referrals through our alumni network of 1 million+ engineers trained since 1997.

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Hold a place on the next batch and sit in on the opening session. See the teaching, the racks and the labs exactly as students do, then enrol if it's right for you.

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Fee

₹30,000

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