CIAI: Cisco Introduction to Artificial Intelligence

CIAI: Cisco Introduction to Artificial Intelligence Certification Training Course Overview

In this 2-day course, Cisco Introduction to Artificial Intelligence (CIAI) v1.0, we will introduce the learner to the Artificial Intelligence, Machine Learning, and Deep Learning essentials in addition to compute platforms such as Cisco UCS, through a combination of lecture and hands-on labs. Artificial Intelligence (AI) and Machine Learning (ML) are opening up new ways for enterprises to solve complex problems, but they will also have a profound effect on the underlying infrastructure and processes of IT. AI/ML is a dominant trend in the enterprise with the ubiquity of large amounts of observed data, the rise of distributed computing frameworks and the prevalence of large hardware-accelerated computing infrastructure became essential.

Target Audience:

The primary audience for this course is as follows:

  • Cisco Integrators/Partners
  • Consulting Systems Engineers
  • Technical Solutions Architects
  • Data Center network professionals (including designers, Administrators, and Engineers), and anyone interested in AI/ML/DL

 

Learning Objectives

Upon completing this course, the learner will be able to meet these overall objectives:

  • Understanding Big Data and Data Science concepts
  • List and describe the concepts, major features, algorithms, and benefits of AI/ML/DL
  • Use AI/ML/DL techniques, such as Neural Networks
  • Get familiar with Data Science and Infrastructure AI Tools and software
  • Describe the Cisco AI/ML/DL Computing Solutions Portfolio alignments

CIAI: Cisco Introduction to Artificial Intelligence (16 Hours) Download Course Contents

Live Virtual Classroom Fee For Both Group Training & 1-on-1 Training On Request
Group Training
08 - 09 Aug 09:00 AM - 05:00 PM CST
(8 Hours/Day)

06 - 07 Sep 09:00 AM - 05:00 PM CST
(8 Hours/Day)

1-on-1 Training (GTR)
4 Hours
8 Hours
Week Days
Week End

Start Time : At any time

12 AM
12 PM

GTR=Guaranteed to Run
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request
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Course Modules

Module 1: Data and AI/ML/DL Fundamentals
  • Introduction to Big Data
  • Introduction to Data Science
  • Introduction to Data Engineering
  • Introduction to Artificial Intelligence (AI)
  • Introduction to Machine Learning (ML)
  • Introduction to Deep Learning (DL)
  • AI/ML/DL Use Cases
Module 2: Artificial Intelligence (AI)
  • AI Concept, Methods, and Techniques
  • Key AI Challenges (Customer and Provider)
  • AI Business Drives
  • Evolution of AI Algorithms
Module 3: Machine Learning (ML)
  • Machine Learning (ML) Algorithms
  • Supervised Learning
  • Unsupervised Learning
Module 4: Deep Learning (DL)
  • Deep Learning Project Phases
  • Custom AI Deep Learning Workflow
  • Deep Learning (DL) Algorithms
Module 5: Neural Networks
  • Neural Networks Fundamentals
  • Neural Architecture Search (NAS)
  • Cisco Neural Architecture Construction (NAC)
Module 6: NLP / NLU
  • Natural Language Processing Basics
  • NLP / NLU Techniques
  • NLP / NLU Deployments
Module 7: Kubernetes
  • What is Kubernetes
  • Introduction to Containers
  • Container Orchestration Engines
  • Kubernetes Basics
  • KubeFlow for AI
Module 8: AI Server Requirements
  • GPU
  • Modern GPU Server Architecture
  • Storage Requirements
Module 9: Data Science and Infrastructure AI Tools
  • Big Data with AI/ML/DL
  • Kubeflow
  • SkyMind SKIL
  • Cloudera Data Science Workbench
  • DL Frameworks > Handwritten Math
  • Kubernetes
  • Demo: Classifying Handwritten Digits with TensorFlow
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Course Prerequisites

Before attending this course, students must have understanding of server design and architecture.