AI-100 Azure AI Engineer Associate, Part 3 of 4: Design AI solutions
Interactive

AI-100 Azure AI Engineer Associate, Part 3 of 4: Design AI solutions

LearnNow Online
Updated May 06, 2021

Course description

Azure AI Engineers work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions. This course covers the Domain Design AI solutions which is (40-45%) of the exam.

Each LearnNowOnline training course is made up of Modules (typically an hour in length). Within each module there are Topics (typically 15-30 minutes each) and Subtopics (typically 2-5 minutes each). There is a Post Exam for each Module that must be passed with a score of 70% or higher to successfully and fully complete the course.


Prerequisites

Candidates for this certification should be proficient in C#, Python, or JavaScript and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure. They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.


Meet the expert

Anand Rao

Anand Rao is a senior technical instructor and cloud consultant. He has worked with large enterprises for about 15 years and has a wide range of technologies in his portfolio.Anand Rao has delivered instructor led trainings in several states in India as well as several countries like USA, Bahrain, Kenya and UAE. He has worked as a Microsoft Certified Trainer globally for Corporate Major Clients.

Video Runtime

96 Minutes

Time to complete

116 Minutes

Course Outline

Design an AI Solution

Define an AI Application Workflow Process (19:18)

  • Introduction (00:08)
  • Define AI Application Workflow Process (03:36)
  • Design a strategy for Ingest and Egress Data (05:56)
  • Design Multiple Workflows and Pipelines (03:00)
  • Design Pipelines that use AI Apps (02:31)
  • Select and AI Solution that Meets Cost Restraints (03:57)
  • Summary (00:08)

Design AI solutions (17:56)

  • Introduction (00:08)
  • Design AI Solutions (06:08)
  • Integrate Bots and AI Solutions (06:51)
  • Design Bot Services that use Language Understandi (04:41)
  • Summary (00:08)

Design Bots that Integrate with Channels (21:36)

  • Introduction (00:08)
  • Design Bots that Integrate with Channels (09:02)
  • Integrate Bots with Azure App Services and Azure (02:19)
  • Identify Computational based Solutions (05:33)
  • Identify Solution Scenarios (04:25)
  • Summary (00:08)

Select a Compute Solution that Meets Cost Constra (17:09)

  • Introduction (00:08)
  • Select a Compute Solution that Meets Cost Constra (07:45)
  • Define How Users and Applications Authenticate to (04:29)
  • Content Moderation Strategy for Data Usage within (04:39)
  • Summary (00:08)

Data Adheres to Compliance Requirements (20:30)

  • Introduction (00:08)
  • Content Moderation Strategy for Data Usage within (04:39)
  • Data Adheres to Compliance Requirements Defined b (01:28)
  • Ensure Appropriate Governance for Data (04:02)
  • Ensure the Solution Meets Data Privacy Stamdards (03:43)
  • Optical Character Recognition Using Python - Lab (06:20)
  • Summary (00:08)
;