Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution (Video)

Description

Plan and manage an AI Azure Solution as you prepare to pass the AI-102 Certification.

This course aligns with the full AI-102 exam objective domain, ensuring complete coverage of every topic:

• Plan and manage an Azure AI solution
• Implement content moderation solutions
• Implement computer vision solutions
• Implement natural language processing solutions
• Implement knowledge mining and document intelligence solutions

This is an important AI certification, centered around solutioning. With Azure AI, businesses can achieve these advancements without needing to build everything from scratch. For the AI-102 certification, understanding this toolkit is key.

The course covers not only how to use Azure AI tools but also how to integrate them responsibly and effectively into real-world solutions. By the end, learners will understand the building blocks of AI and how to deploy them using Microsoft Azure.

Skill Level:

• Intermediate

Learn How To:

• Plan and manage Azure AI Solutions
• Implement content moderation solutions
• Use Azure AI Content Safety for text and image moderation
• Implement computer vision solutions
• Build solutions using Azure AI Vision for image analysis and custom vision models
• Implement Natural Language Processing solutions
• Design and deploy solutions using Azure AI Language and Speech services for text, sentiment analysis, and language translation
• Implement knowledge mining and document intelligence solutions
• Utilize Azure AI Search and Document Intelligence for knowledge discovery and data extraction
• Implement Generative AI Solutions
• Integrate Azure OpenAI Service for content generation and optimization using text, image, and code-based capabilities
• Incorporate the instructors signature study tips, certification strategies, and hands-on demonstrations to ensure mastery of the material

Course Requirements:

Pre-requisites:

• Basic knowledge of Microsoft Azure, AI, and machine learning concepts
• Practical experience in designing and implementing AI and ML solutions using Azure services

Who Should Take This Course:

Job titles:

• Azure AI Engineers
• Data Scientists
• Software Developers and Engineers
• Solution Architects
• IT Professionals and Cloud Administrators

About Pearson Video Training:

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.

Sample Content

Table of Contents

Introduction

Lesson 1: Plan Azure AI Solutions

1.1 Identify appropriate Azure AI services for business scenarios

1.2 Evaluate solution constraints (cost, compliance, scalability)

Lesson 2: Design AI Architectures

2.1 Plan AI solution architecture to meet business requirements

2.2 Configure services for optimal performance

Lesson 3: Manage and Secure AI Solutions

3.1 Implement monitoring and logging for AI services

3.2 Apply security best practices to Azure AI workloads

Lesson 4: Moderate Text Content

4.1 Use Azure AI Content Safety for text moderation

4.2 Automate workflows for compliance reviews

Lesson 5: Moderate Image Content

5.1 Implement image moderation using Azure AI services

5.2 Optimize visual content review processes

Lesson 6: Analyze Images with Pre-Built Models

6.1 Use Azure AI Vision for object detection and analysis

6.2 Detect objects and generate image tags using Azure AI Vision

Lesson 7: Create Custom Computer Vision Models

7.1 Train and deploy custom vision models

7.2 Test and optimize models for domain-specific tasks

Lesson 8: Analyze Video Content

8.1 Implement video indexing and analysis using Azure services

8.2 Extract actionable insights from video content

Lesson 9: Process Text with Azure AI Language

9.1 Perform sentiment analysis and extract key phrases

9.2 Perform text analysis, including sentiment, key phrases, entity recognition, and PII detection

Lesson 10: Build Conversational AI with Bots

10.1 Deploy bots using Azure Bot Framework

10.2 Integrate Question Answering and custom intent models

Lesson 11: Implement Speech-to-Text Solutions

11.1 Use Azure AI Speech to convert speech to text

11.2 Optimize transcription models for accuracy

Lesson 12: Deploy Text-to-Speech Solutions

12.1 Implement text-to-speech solutions for multilingual applications

12.2 Customize voice synthesis using Azure Speech and SSML

Lesson 13: Translate and Localize Content

13.1 Use Azure Translator for multilingual scenarios

13.2 Integrate translation services into applications

Lesson 14: Deploy Knowledge Mining Solutions

14.1 Configure Azure Cognitive Search for knowledge discovery

14.2 Optimize search indexing and relevance

Lesson 15: Extract Data from Documents

15.1 Use Azure Form Recognizer for structured data extraction

15.2 Automate document processing with custom models and integrate document intelligence into Azure AI Search

Lesson 16: Leverage Azure OpenAI Services

16.1 Use GPT models for text generation and summarization

16.2 Use Azure OpenAI models for text, code, and image generation

16.3 Use Azure OpenAI Assistant and implement agents using Azure AI Agent Service

Lesson 17: Optimize Generative AI Models

17.1 Customize pre-trained models for unique use cases

17.2 Integrate generative AI into applications

17.3 Implement orchestration and reflection in agent workflows with Semantic Kernel and Autogen

Lesson 18 Implement Responsible AI Practices

18.1 Ensure fairness and transparency in AI solutions

18.2 Apply privacy and security measures to meet compliance requirements

Lesson 19 Monitor and Optimize Azure AI Solutions

19.1 Instrument services with diagnostics

19.2 Govern cost with workbooks & alerts

19.3 Autoscale & update container deployments

19.4 Trace, collect feedback, and reflect models

Lesson 20 Prepare for the AI-102 Exam

20.1 Use Microsoft Learn, practice tests, and sandboxes

20.2 Study tips and common pitfalls

Updates

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