Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course

AI-102 : Designing and Implementing a Microsoft Azure AI Solution Certification Training Course Overview

The Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course is designed for software engineers and developers who want to implement AI solutions in their applications. This AI-102 course is a four-day instructor-led training program that requires prior experience with software development and some knowledge of AI implementation and tools. It is an intermediate-level course that is ideal for those who know at least one programming language and the workings of Microsoft Azure. Read on to find out some of the other details about this Designing and Implementing Microsoft Azure AI Solution certification training program.

This course prepares you for Exam AI-102. Test your current knowledge Qubits42

Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course (Duration : 32 Hours) Download Course Contents

Live Virtual Classroom
Group Training 1500
01 - 09 Oct GTR 08:30 AM - 12:30 PM CST
(4 Hours/Day)

01 - 04 Nov 09:00 AM - 05:00 PM CST
(8 Hours/Day)

1-on-1 Training (GTR) 1750
4 Hours
8 Hours
Week Days
Weekend

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
Special Solutions for Corporate Clients! Click here
Hire Our Trainers! Click here

Course Modules

Select the appropriate Cognitive Services resource
  • select the appropriate cognitive service for a vision solution
  • select the appropriate cognitive service for a language analysis solution
  • select the appropriate cognitive Service for a decision support solution
  • select the appropriate cognitive service for a speech solution
Plan and configure security for a Cognitive Services solution
  • manage Cognitive Services account keys
  • manage authentication for a resource
  • secure Cognitive Services by using Azure Virtual Network
  • plan for a solution that meets responsible AI principles
Create a Cognitive Services resource
  • create a Cognitive Services resource
  • configure diagnostic logging for a Cognitive Services resource
  • manage Cognitive Services costs
  • monitor a cognitive service
  • implement a privacy policy in Cognitive Services
Plan and implement Cognitive Services containers
  • identify when to deploy to a container
  • containerize Cognitive Services (including Computer Vision API, Face API, Text Analytics, Speech, Form Recognizer)
Analyze images by using the Computer Vision API
  • retrieve image descriptions and tags by using the Computer Vision API
  • identify landmarks and celebrities by using the Computer Vision API
  • detect brands in images by using the Computer Vision API
  • moderate content in images by using the Computer Vision API
  • generate thumbnails by using the Computer Vision API
Extract text from images
  • extract text from images by using the OCR API
  • extract text from images or PDFs by using the Read API
  • convert handwritten text by using Ink Recognizer
  • extract information from forms or receipts by using the pre-built receipt model in Form Recognizer
  • build and optimize a custom model for Form Recognizer
Extract facial information from images
  • detect faces in an image by using the Face API
  • recognize faces in an image by using the Face API
  • configure persons and person groups
  • analyze facial attributes by using the Face API
  • match similar faces by using the Face API
Implement image classification by using the Custom Vision service
  • label images by using the Computer Vision Portal
  • train a custom image classification model in the Custom Vision Portal
  • train a custom image classification model by using the SDK
  • manage model iterations
  • evaluate classification model metrics
  • publish a trained iteration of a model
  • export a model in an appropriate format for a specific target
  • consume a classification model from a client application
  • deploy image classification custom models to containers
Implement an object detection solution by using the Custom Vision service
  • label images with bounding boxes by using the Computer Vision Portal
  • train a custom object detection model by using the Custom Vision Portal
  • train a custom object detection model by using the SDK
  • manage model iterations
  • evaluate object detection model metrics
  • publish a trained iteration of a model
  • consume an object detection model from a client application
  • deploy custom object detection models to containers
Analyze video by using Video Indexer
  • process a video
  • extract insights from a video
  • moderate content in a video
  • customize the Brands model used by Video Indexer
  • customize the Language model used by Video Indexer by using the Custom Speech service
  • customize the Person model used by Video Indexer
  • extract insights from a live stream of video data
Analyze text by using the Text Analytics service
  • retrieve and process key phrases
  • retrieve and process entity information (people, places, urls, etc.)
  • retrieve and process sentiment
  • detect the language used in text
Manage speech by using the Speech service
  • implement text-to-speech
  • customize text-to-speech
  • implement speech-to-text
  • improve speech-to-text accuracy
Translate language
  • translate text by using the Translator service
  • translate speech-to-speech by using the Speech service
  • translate speech-to-text by using the Speech service
Build an initial language model by using Language Understanding Service (LUIS)
  • create intents and entities based on a schema, and then add utterances
  • create complex hierarchical entities
  • use this instead of roles
  • train and deploy a model
Iterate on and optimize a language model by using LUIS
  • implement phrase lists
  • implement a model as a feature (i.e. prebuilt entities)
  • manage punctuation and diacritics
  • implement active learning
  • monitor and correct data imbalances
  • implement patterns
Manage a LUIS model
  • manage collaborators
  • manage versioning
  • publish a model through the portal or in a container
  • export a LUIS package
  • deploy a LUIS package to a container
  • integrate Bot Framework (LUDown) to run outside of the LUIS portal
Implement a Cognitive Search solution
  • create data sources
  • define an index
  • create and run an indexer
  • query an index
  • configure an index to support autocomplete and autosuggest
  • boost results based on relevance
  • implement synonyms
Implement an enrichment pipeline
  • attach a Cognitive Services account to a skillset
  • select and include built-in skills for documents
  • implement custom skills and include them in a skillset
Implement a knowledge store
  • define file projections
  • define object projections
  • define table projections
  • query projections
Manage a Cognitive Search solution
  • provision Cognitive Search
  • configure security for Cognitive Search
  • configure scalability for Cognitive Search
Manage indexing
  • manage re-indexing
  • rebuild indexes
  • schedule indexing
  • monitor indexing
  • implement incremental indexing
  • manage concurrency
  • push data to an index
  • troubleshoot indexing for a pipeline
Create a knowledge base by using QnA Maker
  • create a QnA Maker service
  • create a knowledge base
  • import a knowledge base
  • train and test a knowledge base
  • publish a knowledge base
  • create a multi-turn conversation
  • add alternate phrasing
  • add chit-chat to a knowledge base
  • export a knowledge base
  • add active learning to a knowledge base
  • manage collaborators
Design and implement conversation flow
  • design conversation logic for a bot
  • create and evaluate *.chat file conversations by using the Bot Framework Emulator
  • add language generation for a response
  • design and implement adaptive cards
Create a bot by using the Bot Framework SDK
  • implement dialogs
  • maintain state
  • implement logging for a bot conversation
  • implement a prompt for user input
  • add and review bot telemetry
  • implement a bot-to-human handoff
  • troubleshoot a conversational bot
  • add a custom middleware for processing user messages
  • manage identity and authentication
  • implement channel-specific logic
  • publish a bot
Create a bot by using the Bot Framework Composer
  • implement dialogs
  • maintain state
  • implement logging for a bot conversation
  • implement prompts for user input
  • troubleshoot a conversational bot
  • test a bot by using the Bot Framework Emulator
  • publish a bot
Integrate Cognitive Services into a bot
  • integrate a QnA Maker service
  • integrate a LUIS service
  • integrate a Speech service
  • integrate Dispatch for multiple language models
  • manage keys in app settings file
Download Course Contents

Request More Information

Course Prerequisites
Those who want to apply for the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course need to know at least two programming languages, which are C# and Python.
 
Candidates also need to:
 
  • Know how to use Microsoft Azure
  • Have some experience with JSON and REST programming semantics
  • Have past work experience in application and software development
  • Have an educational background in a related field such as computer science, computer engineering, or software engineering
 

Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course

 
The Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course is ideal for IT professionals, DevOps engineers, and Agile team members. The course teaches learners how to build future-ready applications that are powered by AI. Microsoft Azure is one of the most widely-used service-based platforms for software development, which is why it is a popular and in-demand certification. The Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course uses C# and Python for application development, so those applying for the certification need to be well-versed in the two programming languages.
 
Software engineers and working professionals who want to take up this certification training course will learn how to successfully build, deploy and manage powerful AI solutions provided by Microsoft Azure. AI solutions will help developers optimize their application building process, eliminate unnecessary and excessive processes, and reduce the chances of human error. They will be able to improve the overall development process as well as the quality of the final output.
 
Participants taking up this 2-day Designing and Implementing Microsoft Azure AI Solution course will receive a copy of the AI-102 training material, key resources for the Designing and Implementing Microsoft Azure AI Solution course from Koenig Solutions and Microsoft, access to hands-on lab sessions, and practice tests through the Qubits platform. This Designing and Implementing Microsoft Azure AI Solution course helps participants to prepare for their AI-102 certification exam. The AI-102 certification exam costs USD 165 and can be taken at the Pearson Vue test center.
 

Reasons to choose Designing and Implementing Microsoft Azure AI Solution Certification Training from Koenig Solutions

  • Widely-acknowledged Designing and Implementing Microsoft Azure AI Solution certification training delivered by expert instructors with hands-on lab sessions for you to gain a complete understanding of the concepts
  • Receive Designing and Implementing Microsoft Azure AI Solution (AI-102) course materials in the form of training ppt, access to practice tests through Qubits, practical lab sessions, and more
  • Designing and Implementing Microsoft Azure AI Solution training delivered by  an accredited Microsoft Gold Partner in Koenig Solutions
  • Candidates taking up the AI-102 course are provided multiple practice tests to help them familiarize themselves with the certification exam 
  • Get trained and certified by accredited Microsoft Azure trainers with real-world experience
  • Learners can take up their Designing and Implementing Microsoft Azure AI Solution training on both weekends and weekdays in two different time slots of 4 hours/ day and 8 hours/ day
  • Companies now have the option to customize the AI-102 course according to their business and team requirements
  • Co-participate with other professionals from various job backgrounds and industry sectors to understand how they are using Designing and Implementing Microsoft Azure AI Solution knowledge in their day-to-day work
 

Key Features

  • Instructor-led Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training
  • Get access to a Designing and Implementing Microsoft Azure AI Solution course preview to begin your preparation
  • Expert Microsoft Azure  instructors across the globe
  • Accredited AI-102 course material prepared by SMEs
  • Designing and Implementing Microsoft Azure AI Solution training resources provided to learners from Microsoft 
  • AI-102 course completion certificate provided after the training
  • Participants can take up AI-102 training in 4 different learning modes
  • Designing and Implementing Microsoft Azure AI Solution training provided across 100+ locations globally

Target Audience that can take up Designing and Implementing Microsoft Azure AI Solution Training

Some of the job roles that will benefit from completing the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course are:
  • Software engineers
  • AI developers
  • Web developers
  • App developers
  • UI/UX developers
  • DevOps engineers
  • Agile engineers
  • IT managers
  • Project managers
  • Aspiring Artificial Intelligence Professionals
  • Professionals who are looking to clear their Designing and Implementing Microsoft Azure AI Solution certification exam
 

Learning Objectives

Candidates who complete the certification training course will be able to gain the following skills and knowledge:
  • Knowledge of the requirements to build AI-powered applications
  • Capability to build, deploy and manage application features using AI Cognitive Services
  • Create QnA features for their application
  • Develop applications that can analyze text, are speech-enabled, and have conversational chatbots as well as analyze visual images and videos
  • Use NLP to optimize applications
  • Create customized vision models in their application
  • Learn how to build facial recognition features in their application that can analyze text, face and speech, and also process the text in images and documents
  • Knowledge mining 
 

Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Exam Format

Exam Name : Designing and Implementing Microsoft Azure AI Solution (AI-102) 
Exam Cost : USD 165
Exam Format : Multiple Choice, Scenario-Based, Single Answer
Total Questions : 40-60 Questions
Passing Score : 700 out of 1000
Exam Duration : 130 Minutes
Languages : English
Testing Center : Pearson Vue
 

Skills Measured/Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Examination Weights

  • Implement Computer Vision solutions (20-25%)
  • Implement natural language processing solutions (20-25%)
  • Implement conversational AI solutions (15-20%) 
  • Implement knowledge mining solutions (15-20%)
  • Plan and manage an Azure Cognitive Services solution (15-20%)
 
 

Salary Prospects of a Designing and Implementing Microsoft Azure AI Solution Certified Professional

 
Today, enterprises across the globe are relying on emerging technologies in the form of Artificial Intelligence to automate most of the business processes which require human intervention. To remove complexity, errors and save on cost, businesses have started widespread integration of AI, and in this regard, Designing and Implementing Microsoft Azure AI Solution training gives participants a proper understanding of developing robust AI solutions to their business applications and processes. With the increasing demand of certified professionals in the domain, the AI-102 credential from Microsoft is highly popular. To understand the popularity of the AI-102 credential, let’s check out the salaries of Designing and Implementing Microsoft Azure AI Solution certified professionals from different parts of the world.
 
United States : USD 110,000 to USD 140,000
United Kingdom : Pounds 45,000 to 60,000
India : Rupees 4 lakhs to 15 lakhs 
Australia : AUD 75,000 to 110,000 
UAE : AED 162,000 to 337,000
Singapore :SGD 60,000 to 112,000
 

Job Prospects for Designing and Implementing Microsoft Azure AI Solution Certified Professionals

 
With Artificial Intelligence becoming the most sought-after emerging technology globally, it is increasingly becoming clearer that AI is here to stay. In this regard, Microsoft Azure AI training has become popular as most companies use Azure solutions to host their critical processes on the cloud. There is a high demand for Designing and Implementing Microsoft Azure AI Solution certified professionals across various industry sectors. Some of the top companies hiring Microsoft Azure AI certified professionals include ConvergeOne, Apple, Microsoft, UnitedHealth Group, Exscientia, Mayo Clinic, SYNITI, Collectiv, Ernst & Young, Anthem, and more.
 

 

FAQ's


Yes, fee excludes local taxes.
All modern applications are now becoming AI-powered, which is why completing the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training Course will add immense value to all certified professionals’ resumes. The course begins with an introduction to different services offered by Microsoft Azure to enable AI-powered development. Then candidates will learn how to use different cognitive services, manage and monitor them, and use the cognitive services container. Then the course focuses on NLP (Natural Language Processing) tools for analysis and moves on to creating speech recognition, synthesis and translation modules for their applications.
 
AI-enabled applications are able to understand the user intent with every query, which is something that needs to be built into the application. Azure has a Language Understanding service that helps developers do the same, and this is taught in the course as well. They
To sign up for the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification Training program, candidates have to:
  • Select a schedule for the course based on their availability
  • Enrol for the certification course and choose relevant training delivery mode
  • Attend the Designing and Implementing Microsoft Azure AI Solution instructor-led training
  • Receive the course completion certificate
 
The Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification examination is for USD 165.
No, the cost of the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification training course and the cost of the AI-102 certification exam are both separate.
The Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification is targeted towards software developers, engineers, and AI engineers.
To enroll in the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification training course, participants should follow the given steps:
  • Check course schedules and see which one suits their timings and availability best
  • Enroll by providing all necessary personal and professional information that is required
  • Make the payment to get the course material and begin the learning journey.
 
Yes, the Designing and Implementing Microsoft Azure AI Solution (AI-102) Certification is a prerequisite for candidates if they want to take the Microsoft Certified: Azure AI Engineer Associate certification examination.
Participants can sit for the Designing and Implementing Microsoft Azure AI Solution certification exam at their nearest Pearson Vue test center in person or through the online web-proctored mode.