Certified Microsoft Azure AI Engineer badge achieved after attending the AI-102 Azure AI Engineer Course & Certification
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Microsoft Certified Azure AI Engineer (AI-102) course

Your personal Azure AI Engineer course with everything you need to best prepare for the AI-102 Exam and become a Certified Microsoft Certified Azure AI Engineer, supported by your expert instructor.

course: Microsoft Certified Azure AI Engineer (AI-102)

Duration: 4 days

Format: Virtual or Classroom

prepare-exam Prepares for Exam : Designing and Implementing a Microsoft Azure AI Solution (AI-102)

certification-icon Prepares for Certification : Microsoft Certified: Azure AI Engineer Associate

ktk-icon Attend this and 60+ other Microsoft courses for FREE with Unlimited Microsoft Training

The best course to get your Microsoft Certified Azure AI Engineer Exam and Certification - with Certification Guarantee!

Achieving the Microsoft Certified Azure AI Engineer certification is not an easy task, but with your Readynez Course and Learning Program we’ve done everything we can to support you from start to finish, ensuring you have the optimal conditions to succeed. That includes the best resources available to help you prepare, including relevant online courses, access to practical labs, practice test for Exam prep, study guides, exam support and guides etc, all made easily accessible to you in our Learning Platform. If you select our Virtual Training option, you also contribute to a more sustainable world with a reduction in CO2 emission of 96% compared to the in-classroom option.

  • [Dictionary item: Green-check] Includes a comprehensive set of Learning materials for the best possible Exam prep
  • [Dictionary item: Green-check] Includes access to extensive Labs for 180 days giving you practical hands-on experience
  • [Dictionary item: Green-check] Included in our Unlimited Training offering, giving you access to all our Microsoft courses
  • [Dictionary item: Green-check] Full support available helping you register, prepare for and sit your exam

Who is the Microsoft Certified Azure AI Engineer (AI-102) training course for?

The Microsoft Certified Azure AI Engineer (AI-102) certification is for individuals with experience in designing and implementing AI solutions using Azure tools and services. The certification validates the ability to use Azure Cognitive Services, Machine Learning, and other AI technologies to build intelligent solutions. To obtain the certification, candidates must pass the AI-102 exam, which covers topics such as designing and implementing AI solutions, working with data storage and processing, building and deploying models using Azure Machine Learning, and natural language processing and computer vision technologies.


Feedback from our Microsoft Certified Azure AI Engineer delegates

Stephen Ridgway

Readynez is the best training provider I've used for many years. Their customer service is first class, prices are very competitive and instruction excellent.

Johan Andersson
Johan Andersson

Easy to attend over Teams and an excellent instructor gave me great value for the time I invested.


Everything you need to get the results you want

Your Personal Learning Program will provide the skills you need, to help you do more of what you love. The 3-step learning program is built to teach you real applicable skills that open opportunities for you.


How we get you certified

Readynez365: Your Personal Learning Program

The Readynez365 platform provides an enhanced digital pathway for all your learning elements, from pre-studies to exam, making it the most direct route to new tech Skills. Pick what you want (and need) to get up to speed. It´s all laid out for you in Readynez365 well in advance of your courses.

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Learning Designed For The Virtual Classroom

The training methodology is designed for the virtual classroom to inspire and engage you with a variation of hands-on training, presentations, labs and tests. You’ll also be glad to know that Virtual instructor-led training is loved by managers - it is the most cost-effective way to train.

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Expert Mentoring That Get’s You All The Way

There´s a maximum number of learners in the class to ensure your easy access to personal coaching. You’ll meet accredited expert instructors that are seasoned IT Professionals and Consultants certified to the highest level and bringing real-world experience into the classroom.

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Exam & Skills Focus

We´ll cover the ins and outs of the subject so that you can apply it in your day-to-day work, and you’ll even learn the specifics that you need to know for the exam. It’s your choice whether to sit the exam, or not, but with our detailed guides and hotline, we’ll make it easy to access your exam voucher, and schedule and sit the exam online

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Certification Guarantee

Your access to training is unlimited and you can train as much as you want until you successfully pass your exam.

Sustainable Learning - Train with a Clear Conscience

Train with a clear conscience with training that makes a 96% lower carbon footprint compared to in-classroom training. Our organisation operates with minimal environmental impact and we´ve reduced our Co2 emission with 96% since 2020.We are compliant with the ISO 14001 throughout our entire supply chain as your guarantee for our sustainable business practices.


What you will learn during our Microsoft Certified Azure AI Engineer course

- 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

- 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
- Configure diagnostic logging for a Cognitive Services resource
- Manage Cognitive Services costs
- Monitor a cognitive service
- Implement a privacy policy in Cognitive Services

- Identify when to deploy to a container
- Containerize Cognitive Services (including Computer Vision API, Face API, Text Analytics, Speech, Form Recognizer)

- 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 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

- Build and optimize a custom model for Form Recognizer

- 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

- 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

- 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

- 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

- Retrieve and process key phrases
- Retrieve and process entity information (people, places, urls, etc.)
- Retrieve and process sentiment
- Detect the language used in text

- Implement text-to-speech
- Customize text-to-speech
- Implement speech-to-text
- Improve speech-to-text accuracy

- 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

- 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

- 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 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

- 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

- 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

- Define file projections
- Define object projections
- Define table projections
- Query projections

- Provision Cognitive Search
- Configure security for Cognitive Search
- Configure scalability for Cognitive Search

- 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 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 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

- 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

- 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 a QnA Maker service
- Integrate a LUIS service
- Integrate a Speech service
- Integrate Dispatch for multiple language models
- Manage keys in app settings file


Meet our instructors

Meet some of the Readynez Instructors you can meet on your course. They are experts, passionate about what they do, and dedicated to give back to their industry, their field, and those who want to learn, explore, and advance in their careers.

Julian Sharp
#MVP #Microsoft #Dynamics365

Julian is an official Microsoft Business Application MVP and one of the most widely recognized experts on Dynamics 365.

Jens Gilges
#Microsoft365 #Azure #AWS#AWS #Machine Learning #Ethical Hacking #Penetration Testing #Offsec #GIAC

Jens is a 20-year MCT, an Amazon Authorized Champion Instructor and a well accomplish Cloud Infrastructure Security Consultant and Penetration Tester.


How to best be prepared for our Microsoft Certified Azure AI Engineer course

At Readynez, we provide many resources and have experienced experts in the field. That is why we are also very successful with many satisfied customers. You can therefore safely take your course with us. In order to take the AI-102 Azure AI Engineer certification and course, however, some prerequisites are required.

You have the perfect starting point to take this course with these prerequisites:

  • Proficiency in C#, Python, or JavaScript and ability to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
  • Understanding of the components that make up the Azure AI portfolio and the available data storage options.
  • Candidates need to understand and be able to apply responsible AI principles


Our track record

With 15 years experience and more than 50.000 happy customers from all over the world, companies such as ALSO, ATEA, Microsoft, Serco, and many more, trust Readynez to help them train and certify their staff.

  • [Dictionary item: Green-check] Top rated courses, with learners most often rating their training 10/10
  • [Dictionary item: Green-check] Globally recognized expert instructors, many of which are MVP's
  • [Dictionary item: Green-check] 50.000 delegates trained and certified
  • [Dictionary item: Green-check] Trusted provider of large training projects for many large companies

These are just some of the many major brands trusting Readynez.


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FAQ - Microsoft Certified Azure AI Engineer

A Microsoft Certified Azure AI Engineer is a professional who has demonstrated expertise in designing and implementing AI solutions on the Microsoft Azure platform. This certification validates the individual's skills in leveraging Azure AI services to build AI models, implement natural language processing (NLP), and integrate AI solutions into Azure applications.

Microsoft Azure AI-102 exam comprises 40-60 questions of different types such as multiple-choice questions, scenario-based single-answer questions, arranged in the correct sequence type questions, mark review, drag & drop questions, and so on.

The AI-102 certification exam is priced at $165.

The passing score for the AI-102 exam (Microsoft Certified: Azure AI Engineer) is typically 700 out of 1000 points.

The time limit for the AI-102 exam (Microsoft Certified: Azure AI Engineer) is 180 minutes (3 hours).

The Microsoft Certified Azure AI Engineer certification is typically considered valid for two years.

Microsoft will send a reminder email six months before the certificate expiration date for renewal. It is essential to renew your certification before it expires to avoid retaking the exam and incurring additional costs.

The AI-102 exam does not have specific prerequisites, but it is recommended that candidates have knowledge and experience in certain areas before attempting the exam. Microsoft suggests that candidates should have practical experience designing and implementing AI solutions on Azure, including:

  • Translating requirements into an AI solution.
  • Designing and implementing AI models using Azure services.
  • Implementing natural language processing (NLP) workloads on Azure.
  • Integrating AI models into applications and services.

While the AI-102 exam (Microsoft Certified: Azure AI Engineer Associate) doesn't mandate specific prerequisites, candidates are strongly advised to possess practical experience in crafting and implementing AI solutions on Azure. The exam evaluates hands-on skills in utilizing Azure AI services. Proficiency in translating business requirements into AI solutions, designing and implementing AI models on Azure, implementing NLP workloads, and integrating AI models into applications is beneficial.

The difficulty of the AI-102 exam (Microsoft Certified: Azure AI Engineer) can vary based on an individual's experience, skills, and preparation. For candidates with a solid understanding of Azure services, hands-on experience in designing and implementing AI solutions, and familiarity with related technologies, the exam may be more manageable.

The duration needed to prepare for the AI-102 exam (Microsoft Certified: Azure AI Engineer) is contingent on an individual's existing knowledge, familiarity with Azure services, and the study time they allocate. Generally, candidates invest several weeks to a few months in exam preparation. The variability is influenced by factors such as study approach, time commitment, and individual learning style.

Specific salary figures for individuals holding the Microsoft Certified: Azure AI Engineer Associate (AI-102) certification can vary based on factors such as location, experience, industry, and the specific job role. The certification validates expertise in designing and implementing AI solutions on the Azure platform.

On average, professionals with AI and Azure expertise tend to command competitive salaries, often above the industry average for IT roles. As of 2021, a Microsoft Certified: Azure AI Engineer could expect a salary ranging from $90,000 to $130,000 annually, depending on the factors mentioned earlier.

The value of the Microsoft Certified: Azure AI Engineer Associate (AI-102) certification varies based on individual career goals, interests, and industry demands. Earning this certification can unlock diverse career opportunities, showcasing expertise in designing and implementing AI solutions on Azure. It serves as a recognized validation of skills, providing a competitive advantage in job markets where Azure certifications are highly valued. Additionally, the certification journey enhances knowledge through hands-on practice and aligns professionals with industry best practices, contributing to continuous professional development.

The AI-102 exam, a component of Microsoft Certified: Azure AI Engineer Associate, adopts a computer-based testing format. To initiate the process, candidates register via the official Microsoft Certification website. Subsequently, scheduling is facilitated through exam providers like Pearson VUE, offering flexibility for both in-person and online examination options.

This computer-based format encompasses various question types, including multiple-choice, case studies, and scenario-based questions. For candidates opting for online exams, adherence to specified technical requirements is imperative. The examination day involves a check-in process that includes ID verification before candidates embark on the timed test.

Prepare for the AI-102 certification exam by understanding Microsoft's official exam objectives and using diverse study materials like documentation and recommended resources. Enroll in online courses for structured learning and hands-on practice through virtual labs or Azure services. Take practice exams to assess your knowledge, engage with the AI community, and stay informed about industry trends. Manage time effectively, review progress regularly, and adapt your study plan to reinforce theoretical knowledge with practical experience. Stay updated on Azure AI services and potential changes to the exam format.

The Microsoft Certified: Azure AI Engineer Associate (AI-102) certification can open doors to various job opportunities in the field of artificial intelligence and cloud computing. Here are some potential roles:

  • AI Engineer: As a specialized AI Engineer, you can design and implement AI solutions using Azure services, contributing to the development of intelligent applications.
  • Machine Learning Engineer: Work on machine learning models and algorithms, leveraging Azure's machine learning capabilities to create predictive and analytical solutions.
  • Data Scientist: Apply AI and machine learning techniques to analyze and interpret complex datasets, helping organizations make data-driven decisions.

The AI-102 certification exam, part of Microsoft Certified: Azure AI Engineer Associate, can be taken through Pearson VUE, the authorized exam delivery provider for Microsoft certifications.

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