Course Description

Artificial Intelligence (AI) and Machine Learning (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 infrastructures. There are several compute platforms designed and purpose-built for Deep Learning (DL). These platforms should be storage and I/O-optimized to deliver industry-leading performance to speed up Deep Learning (DL) using neural networks and large data sets to train computers for complex tasks. The CIAI - Cisco Introduction to Artificial Intelligence instructor-led course introduces the learner to the Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) essentials in addition to compute platforms such as Cisco UCS, through a combination of lecture and hands-on labs.

Objectives

• Understand Big Data and Data Science concepts
• List and describe the concepts, major features, algorithms, and benefits of AL/ML/DL
• Use AL/ML/DL techniques, such as Neural Networks.
• Get familiar with Data Science and Infrastructure AI Tools and soft wares
• Describe the Cisco AI/ML/DL Computing Solutions Portfolio alignment
• Describe the Cisco UCS C480 ML M5 Deep Learning Server

Audience

• Cisco Integrators/Partners
• Consulting Systems Engineers
• Technical Solutions Architects
• Data Center Administrators and Engineers
• Anyone interested in AI/ML/DL

Prerequisites

The knowledge and skills that a learner should have before attending this course include:

• Understanding of server design and architecture.
• Familiarity with Cisco UCS, Storage, and Server Virtualization

Content

Virtual Classroom Live Outline

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

Artificial Intelligence (AI)

• AI Concept, Methods, and Techniques
• Key AI Challenges (Customer and Provider)
• AI Business Drives
• Evolution of AI Algorithms

Machine Learning (ML)

• Machine Learning (ML) Algorithms
• Supervised Learning
• Unsupervised Learning

Deep Learning (DL)

• Deep Learning Project Phases
• Custom AI Deep Learning Workflow
• Deep Learning (DL) Algorithms

Neural Networks

• Neural Networks Fundamentals
• Neural Architecture Search (NAS)
• Cisco Neural Architecture Construction (NAC)

Data Science and Infrastructure AI Tools

• Big Data with AI/ML/DL
• Kubeflow
• SkyMind SKIL
• Cloudera Data Science Workbench
• DL Frameworks > Handwritten Math
• Kubernetes
• Skymind SKIL
• Demo: Classifying Handwritten Digits with TensorFlow

Cisco Computing Solutions/UCS AI/ML/DL Portfolio

• The Big data journey
• Cisco Computing Solutions for AI
• Test, development, and model tuning
  • Cisco HyperFlex HX24 and Cisco UCS C240 M5
• Machine learning and deep learning
  • Cisco UCS C480 ML M5
• Inferencing
  • Cisco HyperFlex HX240
  • Cisco UCS C220 M5 andCisco UCS C240 M

Cisco UCS C480 ML Rack Server

• Cisco UCS C480 ML M5 Overview
• Cisco UCS C480 ML M5 Features and Benefits
  • System Front and Rear View
  • CPU, GPU, and IO Module
  • Internal NVLink Topology
  • Storage Options – RAID Card and Drives
  • Connectivity with Lan on Motherboard (LoM)
• Cisco UCS C480 ML M5 Management
  • Integrated Management Controller (IMC) – OoBM
  • Cisco UCS Unified Management
  • Cisco Intersight (cloud-based)
• Cisco UCS C480 ML M5 Deployment
  • Standalone
  • Cisco UCS managed environment.
• Cisco UCS C480ML Rack Server for Deep Learning

Virtual Classroom Live Labs

Lab 1: Deep Learning Framework Setup (TensorFlow and Jupyter Stack)
Lab 2: Classifying Handwritten Digits with TensorFlow
Lab 3: DL Chatbot - Training a Model to Have a Conversation with a Google Chatbot similar to Alexa or Siri
Lab 4: ML Training a Machine to play "The Snake Game"