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IT & Software IT Certification Microsoft Certification

AI-100: Designing and Implementing an Azure AI Solutions

Clear and Concise
Bestseller
Rating: 4.3 out of 54.3 (112 ratings)
4,100 students
Created by Anand Rao Nednur
Last updated 4/2021
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Ingest, transform, and prepare data for AI solutions
  • Design and implement end-to-end AI solutions on Microsoft Azure
  • Monitor and optimize AI solutions deployed on Microsoft Azure
  • Secure AI solutions on Microsoft Azure
  • You will be able to integrate and get best results for any computer vision or Natural Language processing tasks.
  • Ability to show and include Machine Learning applications in your app
  • Learn Microsoft Azure - Cloud platform cognitive services like Face, Vision, Text API
Curated for the Udemy for Business collection

Requirements

  • This path is intended for learners who are familiar with common AI workflows and concepts, but who do not have experience applying these concepts using Microsoft Azure services.
  • Basic Python or Javascript
  • Basic idea about HTTP, REST
  • Usage of Visual Studio

Description

UPDATE : Please note that this course will be upgraded to AI 102 with the new curriculum.

This means that even if you are preparing for AI 100, you can continue to use this course for AI 102 preparation.

---------------------------------------------------------------------------------------------------------------------------------------------------------

Microsoft Azure offers a spread of services designed to work together to enable rapid development of high-performance AI solutions. This skill teaches how these Azure services work together to enable you to design, implement, operationalize, monitor, optimize, and secure your AI solutions on Microsoft Azure. This path is designed to address the Microsoft AI-100 certification exam.

This course covers Azure Cognitive APIs for Visual Features including Face Detection, Tagging the content of an image, OCR as well as Text Analytics for Language Detection, Sentiment Analysis and Key Phrase extraction. The course is very hands on and covers the implementation of these APIs using Python as well as Javascript.

With cognitive services you will be able to build all such or even more types of applications.

Here is the course content covered in this course :


Analyze solution requirements (25-30%)

Recommend Azure Cognitive Services APIs to meet business requirements

· select the processing architecture for a solution

· select the appropriate data processing technologies

· select the appropriate AI models and services

· identify components and technologies required to connect service endpoints

· identify automation requirements Map security requirements to tools, technologies, and processes · identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements

· identify which users and groups have access to information and interfaces

· identify appropriate tools for a solution

· identify auditing requirements Select the software, services, and storage required to support a solution

· identify appropriate services and tools for a solution

· identify integration points with other Microsoft services

· identify storage required to store logging, bot state data, and Azure Cognitive Services output

Design AI solutions (40-45%)

Design solutions that include one or more pipelines

· define an AI application workflow process

· design a strategy for ingest and egress data

· design the integration point between multiple workflows and pipelines

· design pipelines that use AI apps

· design pipelines that call Azure Machine Learning models

· select an AI solution that meet cost constraints Design solutions that uses Cognitive Services

· design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs Design solutions that implement the Microsoft Bot Framework

· integrate bots and AI solutions

· design bot services that use Language Understanding (LUIS)

· design bots that integrate with channels

· integrate bots with Azure app services and Azure Application Insights Design the compute infrastructure to support a solution

· identify whether to create a GPU, FPGA, or CPU-based solution

· identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure

· select a compute solution that meets cost constraints Design for data governance, compliance, integrity, and security

· define how users and applications will authenticate to AI services

· design a content moderation strategy for data usage within an AI solution

· ensure that data adheres to compliance requirements defined by your organization

· ensure appropriate governance of data

· design strategies to ensure that the solution meets data privacy regulations and industry standards

Implement and monitor AI solutions (25-30%)

Implement an AI workflow

· develop AI pipelines

· manage the flow of data through the solution components

· implement data logging processes

· define and construct interfaces for custom AI services

· create solution endpoints

· develop streaming solutions Integrate AI services and solution components

· configure prerequisite components and input datasets to allow the consumption of Azure Cognitive Services APIs

· configure integration with Azure Cognitive Services

· configure prerequisite components to allow connectivity to the Microsoft Bot Framework

· implement Azure Cognitive Search in a solution Monitor and evaluate the AI environment

· identify the differences between KPIs, reported metrics, and root causes of the differences

· identify the differences between expected and actual workflow throughput

· maintain an AI solution for continuous improvement

· monitor AI components for availability

· recommend changes to an AI solution based on performance data


Hope this course would be informative to you. Please reach out to me if you have any questions.

Who this course is for:

  • Participants who intend to learn common AI workflows and concepts
  • Participants who want to Secure AI solutions
  • Participants preparing for AI 100 Microsoft Certification

Course content

5 sections • 59 lectures • 5h 0m total length

  • Preview02:17

  • What Can you Expect in this Section
    00:51
  • Preview10:37
  • Preview05:01
  • Preview15:29
  • Preview05:14
  • Preview10:58
  • Preview07:15
  • Preview07:13

  • Preview06:15
  • Preview03:23
  • Select the appropriate AI models and services
    06:52
  • Identify components and technologies required to connect service endpoints
    04:54
  • Identify automation requirements
    03:07
  • Introduction to Cognitive Services - Lab Activity
    04:46
  • Identify Processes and Regulations Needed to Conform with Data Privacy
    03:09
  • Identify which Users and Groups have Access to Information and Interfaces
    04:02
  • Identify Appropriate Tools for a Solution
    03:42
  • Identify Auditing Requirements
    04:48
  • Identify appropriate services and tools for a solution
    04:59
  • Identify integration points with other Microsoft services
    05:41
  • Identify storage required to store logging, bot state data, and Azure Cognitive
    04:36
  • Face Recognition Lab Activity
    12:50
  • Group Picture -Detection- Lab Activity
    07:24

  • Preview03:40
  • Design a Strategy for Ingest and Egress Data
    05:56
  • Design the integration point between multiple workflows and pipelines
    03:05
  • Design Pipelines that use AI Apps
    02:31
  • Select an AI Solution that Meets Cost Restraints
    03:57
  • Design solutions that use vision, speech, language, knowledge, search etc
    06:11
  • Integrate Bots and AI Solutions
    06:51
  • Design Bot Services that use Language Understanding (LUIS)
    04:45
  • Design Bots that Integrate with Channels
    09:10
  • Integrate Bots with Azure App Services and Azure Application Insights
    02:25
  • Identify Whether to Create a GPU, FPGA, or CPU-Based Solution
    05:33
  • Identify Whether to Use a Cloud-Based, On-Premises, or Hybrid Compute Infra
    04:31
  • Select a Compute Solution that Meets Cost Constraints
    07:50
  • 31 Define how users and applications autenticate to AI services
    04:33
  • 32 Design a Content Moderation Strategy for Data Usage within an AI Solution
    04:48
  • 33 Ensure that Data Adheres to Compliance Requirements Defined by an Organizatio
    01:32
  • 34 Ensure Appropriate Governance for Data
    04:08
  • 35 Design Strategies to Ensure the Solution Meets Data Privacy and Industry Stan
    03:47
  • Optical Character Recognition Using Python - Lab Activity
    06:21

  • 36 Develop AI Pipelines
    05:05
  • 37 Manage the Flow of Data Through Solution Components
    03:17
  • Implement Data Logging Processes
    02:37
  • Define and Construct interfaces for Custom AI Services
    08:16
  • Integrate AI Models with other Solutions Components
    03:10
  • Create Solution Endpoints
    02:00
  • Develop Streaming Solutions
    05:17
  • Configure Prerequisite Component and Input Datasets to Allow Consumption of data
    03:19
  • Configure Integration with Azure Services
    02:16
  • Implement Azure Search in a Solution
    03:40
  • Identify the Differences Between KPIs, Reported Metrics, and Root Causes
    03:43
  • Identify the Differences Between Expected and Actual Workflow Throughput
    03:52
  • Implement AI for Continuous Improvement
    03:22
  • Monitor AI Components for Availability
    07:00
  • Recommend Changes to an AI Solution Based on Performance Data
    05:11
  • Course Conclusion - AI 100
    01:20

Instructor

Anand Rao Nednur
Cloud Architect on AWS, Azure and GCP
Anand Rao Nednur
  • 4.3 Instructor Rating
  • 6,460 Reviews
  • 106,255 Students
  • 25 Courses

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 is adept at not just cloud platforms (Azure , AWS and GCP) but also well-versed with IAM, security and automation with powershell and python.

In addition, he has been developing and updating the content for various courses. He has been assisting many engineers in the lab examinations and securing certifications.

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.

Anand is also a Certified seasoned professional holding certifications in following platforms:

     Microsoft Certified Trainer ( MCT )
     SY0-401 : CompTIA Security +
     Scrum Certified master ( SCRUM )
     ITIL V3 
     Certified Network Defender ( CND – EC-Council )

     Certified Ethical hacker  ( CEH – EC-Council )
     70-640 MS Active Directory
     70-533 MS Azure Administration
     70-534 MS Azure Architecture
     AWS certified solutions Architect – Associate
     AWS certified sysops administrator – Associate
     Google Cloud Platform-Cloud Architect (GCP)
     Certified Cloud Security Knowledge ( CCSK )


Note: Anand also manages channel "The Cloud Mentor" in youtube. Feel free to subscribe to AWS and Azure. Share, Learn, Subscribe. 

WWW.THECLOUDMENTOR.COM

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