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Microsoft Certified Azure AI Engineer Associate: AI 102

Develop and Deploy AI Solutions with Microsoft Azure
  • Aligned with the Microsoft Certified: Azure AI Engineer Associate (AI-102) training.
  • Access practice tests to excel in the AI-102 exam.
  • Develop AI apps with Azure services like AI Search and OpenAI.
  • Master computer vision, NLP, and speech services.
  • Leverage Azure to deploy intelligent applications.

Course Overview

The Azure AI certification course equips you for Microsoft’s AI-102 Azure AI Engineer Associate exam. It delves into Azure services such as language, speech, translation, OpenAI, prompt engineering, and responsible generative AI. Additionally, it provides in-depth knowledge of Azure Cognitive Services, Azure Cognitive Search, and the Microsoft Bot Framework.

Key Features

Comprehensive training aligned with the AI-102 certification for Azure AI Engineer Associate

Access to official Microsoft handbooks designed specifically for the AI-102 examination

Prepare effectively with targeted practice tests to ensure exam success

Learn from Microsoft-certified trainers through hands-on training sessions

Gain practical experience through labs and projects within Azure Labs

Earn an official course completion badge or certificate hosted on the Microsoft Learn portal

Skills Covered

Training options

Online Bootcamp

.
  • Flexi Pass Enabled: Flexibility to reschedule your cohort within first 90 days of access.
  • Live, online classroom training by top instructors and practitioners
  • 24x7 learner assistance and support
Preferred

Corporate Training

Upskill or reskill your teams
  • Blended learning delivery model (self-paced e-learning and/or instructor-led options)
  • Course, category, and all-access pricing
  • Enterprise-class learning management system (LMS)
  • Enhanced reporting for individuals and teams
  • 24x7 teaching assistance and support

Eligibility

The online Microsoft Certified Azure AI Engineer Associate course is designed for experienced programmers aiming to build AI-powered applications using Azure services. Participants are expected to have knowledge of Python or C#, REST API principles, JSON, and Azure service solutions.

Pre-requisites

Familiarity with the Microsoft Azure portal and services, along with proficiency in programming languages such as Python or C#, is recommended for enrolling in this program. A solid understanding of REST APIs and JSON, combined with a willingness to explore Azure Cognitive Services, will enable you to excel in this course more efficiently.

Course Content

Developing AI Solutions on Azure

Preparing to Develop AI Solutions on Azure

  • Explore the capabilities of Azure Machine Learning
  • Understand Azure AI Services
  • Learn about Azure OpenAI Service features
  • Discover Azure AI Search capabilities

Creating and Consuming Azure AI Services

  • Set up Azure AI service resources within a subscription
  • Identify service endpoints, keys, and locations
  • Utilize REST APIs and SDKs to consume Azure AI services
Securing and Monitoring AI Solutions

Securing Azure AI Services

  • Implement authentication methods for Azure AI services
  • Manage network security for Azure AI environments

Monitoring Azure AI Services

  • Track service costs and monitor usage
  • Set up alerts and review service metrics
  • Manage diagnostic logging for services
Deploying and Analyzing AI Solutions

Deploying Azure AI Services in Containers

  • Create reusable container resources
  • Deploy and secure containers
  • Utilize Azure AI services from containers

Analyzing Images and Videos

  • Set up an Azure AI Vision resource
  • Analyze images and generate smart-cropped thumbnails
  • Extract insights from videos using Azure Video Indexer
AI Solutions for Vision and Language
Classifying and Detecting Images
  • Train image classifiers with Custom Vision
  • Detect and analyze faces with Computer Vision
  • Implement facial recognition using Azure Face service
Reading and Analyzing Text
  • Extract text using OCR from images and documents
  • Detect languages and analyze sentiment from text
  • Extract key phrases and entities using Azure AI Language
Creating Conversational AI Solutions
Building Question-Answering Solutions
  • Create and publish knowledge bases
  • Implement multi-turn conversations with active learning
  • Develop bots for question-answering applications
Developing Conversational Language Models
  • Define intents, utterances, and entities
  • Utilize pre-built entity components
  • Train, test, and publish language models
Advanced Text and Speech Solutions

Creating Custom Text Classification and Entity Recognition

  • Develop custom text classification models
  • Tag data and deploy classification tasks
  • Build projects for named entity recognition

Implementing Speech-Enabled Apps and Translation

  • Use Azure Speech-to-Text and Text-to-Speech APIs
  • Configure SSML for advanced speech synthesis
  • Translate speech and generate spoken translations
Building Search and Knowledge Solutions
Creating and Customizing AI Search Solutions:
  • Develop search applications with AI capabilities
  • Integrate custom skills into search skillsets
  • Build knowledge stores from search pipelines
Planning and Utilizing Document Intelligence Solutions:
  • Explore components of Document Intelligence
  • Use pre-built models to analyze forms and documents
  • Extract data with SDKs and REST APIs
Azure OpenAI Solutions and Generative AI
Working with Azure OpenAI Service:
  • Create and test models using Azure OpenAI
  • Build applications using OpenAI endpoints
  • Apply prompt engineering techniques effectively
Generating Code, Images, and RAG Solutions:
  • Use prompts to generate code and documentation
  • Integrate DALL-E for image generation within apps
  • Implement Retrieval Augmented Generation (RAG) with custom data
Responsible AI and Governance
Principles of Responsible Generative AI:
  • Develop processes for responsible AI solutions
  • Identify and mitigate potential AI-related harms
  • Deploy and manage AI solutions responsibly
Governance and Risk Management for AI:
  • Establish governance policies for AI solutions
  • Manage risks with responsible AI practices

Exam & Certification

What benefits do learners receive from Microsoft Azure by attending the course ?

  • Learners receive a course completion badge/certificate on the Microsoft Learn portal.
  • Access to official Microsoft handbooks aligned to the AI-102 examination.

What is required to earn the Azure AI Engineer Associate certification?

To earn the certification, learners must pass the AI-102: Azure AI Engineer Associate exam.

Does this new exam and certification replace any existing Azure exams?

Yes, AI-102 replaces the AI-100 exam, which expired on June 30, 2021.

Do you provide any practice tests as part of this AI-102 course?

Yes, practice tests are included to help students prepare for the AI-102 exam, simulating the types of questions they will encounter.

When will the old Azure certification competencies expire, and when will the new requirements become valid?

The new AI-102 format went live in February 2021. Review the change log before taking the exam.

Is the exam fee included in the course fee?

No, the exam fee is not included in the course fee.

How much does the Microsoft Azure AI Engineer certification exam cost?

The exam costs $165 plus applicable taxes. This fee is paid to Microsoft during registration.

Do you assist in the exam application process?

Yes, the Help and Support team can assist with the application process.

How can I pass the Microsoft AI Engineer exams on my first attempt?

This AI-102 course equips you with the necessary skills and knowledge to complete projects and prepare thoroughly for the AI-102 exam. While success on the first attempt is not guaranteed, learners will be well-prepared for the exam.

FAQs

How much does a Microsoft certified Azure AI engineer associate make?
According to Glassdoor, certified Azure AI engineer associates earn an average of INR 11.5 LPA to 12.4 LPA in India.
What is Microsoft AI-102 certification?
Microsoft AI-102 certification equips professionals with the skills to design and implement AI solutions using Azure. It covers NLP, computer vision, machine learning, Azure Cognitive Services, and practical projects to validate expertise.
What does an AI engineer do?
AI engineers design and build AI models and systems, working with machine learning algorithms, neural networks, and NLP. They collaborate with data scientists and developers to ensure efficient deployment and scalability of AI solutions.
What are the benefits of the AI-102 certification course?
The AI-102 course offers specialized training in NLP, computer vision, and machine learning. It includes hands-on projects, career assistance, and tools to help learners build AI-powered applications and enhance job prospects.
How efficient are the trainers at BELLS?
BELLS’s instructors are industry experts with extensive AI and ML experience. Their teaching blends academic knowledge and real-world insights, providing learners with highly relevant and practical learning experiences.
How do I enroll in the Azure AI engineer certification training?
To enroll, follow these steps:
  • Complete the online application form by selecting the “Enroll Now” option.
  • Make secure payment using credit/debit cards, PayPal, or other supported methods.
  • Once payment is processed, access details will be sent via email.
What career paths can I pursue after completing the AI-102 certification?
With AI-102 certification, learners can pursue roles such as AI engineer, ML engineer, or AI solutions architect. Advanced roles include AI project manager or consultant, with opportunities to specialize in NLP, computer vision, or conversational AI.
Does BELLS offer corporate training solutions?
Yes, BELLS offers custom corporate training solutions for talent development, including certifications and role-based learning. They provide access to their learning library through the Learning Hub+ platform for continuous learning.
Is the AI-102 certification worth it?
Yes, the AI-102 certification validates expertise in AI and Azure services, enhancing career prospects in AI roles. It equips professionals with skills in machine learning, NLP, and computer vision, meeting the rising demand for AI specialists.
What are the prerequisites for the AI-102 exam?
While there are no formal prerequisites, familiarity with Azure AI services and prior certifications like AZ-900 (Azure Fundamentals) can be beneficial.
How do I become an Azure AI engineer?
Start by building strong programming skills in Python and C#. Enroll in BELLS’ Azure AI certification program to gain hands-on experience with AI tools, workflows, and model deployment.
Which companies hire AI engineers?
Major tech firms like Google, Microsoft, Amazon, and IBM actively hire AI engineers. Industries such as finance (JPMorgan Chase), healthcare (GE Healthcare), and automotive (Tesla) also seek AI talent for various innovative projects.

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