Exam Prep AI-102: Microsoft Azure AI Engineer Associate
- Offered byCoursera
Exam Prep AI-102: Microsoft Azure AI Engineer Associate at Coursera Overview
Duration | 15 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course |
Credential | Certificate |
Exam Prep AI-102: Microsoft Azure AI Engineer Associate at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Intermediate Level Skilled in C Python language and able to leverage REST-based APIs & SDK to build Computer Vision, NLP, Knowledge Mining & Conversational AI Solutions
- Approx. 15 hours to complete
- English Subtitles: English
Exam Prep AI-102: Microsoft Azure AI Engineer Associate at Coursera Course details
- The AI-102: Designing and Implementing a Microsoft Azure AI Solution certification exam tests the candidate experience and knowledge of the AI solutions that make the most of Azure Cognitive Services and Azure services. In addition, the exam also tests the candidate's ability to implement this knowledge by participating in all phases of AI solutions development—from defining requirements, and design to development, deployment, integration, maintenance, performance tuning, and monitoring.
- Take this Designing and Implementing a Microsoft Azure AI Solution: AI-102 exam and become a part of the futuristic world of Artificial Intelligence and grow your career by attaining Azure AI-102 certification.
- Azure AI engineers have experience developing solutions that use languages such as Python or C# and should be able to use REST-based APIs and software development kits (SDKs) to build secure image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI solutions on Azure. They should be familiar with all methods of implementing AI solutions. Plus, they understand the components that make up the Azure AI portfolio and the available data storage options. Azure AI engineers also need to understand and be able to apply responsible AI principles.
- This course contains 5+ hours of training videos. Learners could find a total of 90+ lectures in the training course with comprehensive coverage of all topics regarding the exam AI-102: Designing and Implementing a Microsoft Azure AI Solution. These lectures are divided into 5 Modules and each module is further split into lessons. The entire course includes Assessments to validate knowledge checks of learners. Also, a set of Graded Questions is available at the end of every module.
- Module 1: Azure AI Solutions: Planning and Management
- Module 2: Image & Video Processing Solutions
- Module 3: Natural Language Processing (NLP) Solutions
- Module 4: Knowledge Mining Solutions
- Module 5: Conversational AI Solutions
- Enroll in Exam Prep AI-102: Microsoft Azure AI Engineer Associate Course and advance your Azure AI Solution Workload skills with Microsoft Azure.
- This training course helps you develop your skills and knowledge in AI-102. You can start with fundamental certifications such as the AI-900 exam. Once you gain command over all phases of AI solutions development, you are ready to start preparing for the AI-102 exam.
- This AI-102 course is mainly for those who need opportunities in various job roles such as Cloud Developers, Cloud Engineers, Solutions Architects, and Cloud Architects.
- By the end of this course, you will be able to pass the AI-102 exam on the first attempt and master Designing and Implementing a Microsoft Azure AI Solution.
Exam Prep AI-102: Microsoft Azure AI Engineer Associate at Coursera Curriculum
Azure AI solutions: Planning and Management
About the Course
Prerequisites for Attending this Course
What are Azure AI Solutions?
Python Installation
What are Cognitive Services?
Cognitive Services for a Vision Solution
Cognitive Services for a Language Analysis Solution
Cognitive Services for a Decision Support Solution
Cognitive Services for a Speech Solution
Manage account keys & Authentication
Manage account keys & Authentication - Demo
Azure Virtual Networks
Azure Virtual Networks - Demo
Responsible AI principles
Create an Azure AI resource
Create an Azure AI resource - Demo
Configure diagnostic logging
Configure diagnostic logging - Demo
Manage costs for Azure AI services
Manage costs for Azure AI services - Demo
Monitor an Azure AI resource
Monitor an Azure AI resource - Demo
CI/CD Integration
Working with Containers
Anomaly Detector
Anomaly Detector - Demo
Azure Content Moderator
Azure Content Moderator - Demo
Personalizer
Azure Metrics Advisor
Azure Immersive Reader
Azure Immersive Reader - Demo
Welcome to the Course
Course Outline
Azure AI solutions: Planning and Management - Course Overview
Azure AI Engineer Associate - Knowledge Check
Azure AI services : Appropriate Selection and Security - Knowledge Check
Azure AI services : Appropriate Selection and Security - Knowledge Check
Detecting Anomalies & Improving Content - Knowledge Check
Azure AI solutions: Planning and Management - Assessment
Image & Video Processing Solutions
Computer Vision
OCR - Text Extraction
Azure Form Recognizer
Azure Form Recognizer -Demo
Azure Video Indexer
Azure Video Indexer - Demo
Image Calssification & Object Detection
Image Calssification & Object Detection - Demo
Creating a Custom Model
Training a Custom Model
Creating and Training a Custom Model - Demo
Model Evaluation
Model Evaluation & Testing - Demo
Model Exporting
Model Exporting - Demo
Image & Video Processing Solutions Overview
Analyze Text Extractor and Azure Video Indexer - Knowledge Check
Image Classification & Object Detection - Knowledge Check
Image & Video Processing Solutions - Assessment
Natural Language Processing (NLP) Solutions
Analyze Text : Key Phrases
Analyze Text : Entities
Analyze Text : Sentiment
Analyze Text : Language Detection
Demo: Cognitive Services and Text Analytics with Visual Studio Code
Demo: Azure Text Analytics with Visual Studio Code
Process Speech: Text-to-Speech
Process Speech: Speech-to-Text
Process Speech: Keyword & Intent Recognition
Demo: Text Translation Setup with Cognitive Services & Translator
Demo: Translate Text with Translator Service - Configure and Run
Azure Translator Service
Translate Speech-to-speech using Azure Services
Azure Speech-to-Text Translation
Custom Translation Models
Demo - Translate Speech-to-Speech: Creating and Deploying Cognitive Resource
Demo - Translate Speech to Speech: Configuring Speech Recognition and Synthesis
Demo - Translating Text-to-Speech: Configuring Repository Cloning, Visual Studio, and Cognitive Service
Demo - Translating Text-to-Speech: Configuring Resource Group Connection, Visual Studio Setup, and Code Execution
Language Understanding Model : Create Intents and Add Utterances
Language Understanding Model : Create Entities
Language Understanding Model : Train, Evaluate, Deploy, and Test
Language Understanding Model : Optimize a Language Understanding model
Language Understanding Model : Integrate multiple language service model
Language Understanding Model- Import and Export language understand
Demo - Conversational Language Model: Creating Language Service Resource & Conversation Understand
Demo - Conversational Language Model : Training & Deployment with Performance Analysis
Demo - Conversational Language Model : Creating a Schema Definition and Training a Conversational Language Model
Demo - Conversational Language Model : Testing a Conversational Language Model
Creating a Question Answering Project and a Source
Creating Conversational Q&A Solution - Train and test a knowledge base
Exporting Publishing a knowledge base
Creating Web Chat Bot
Create a multi-turn conversation
Adding chit-chat to a Knowledge Base
Demo - Conversational Language Understanding Project using Azure Language Studio
Demo - Deploying and Testing Azure LUIS Conversational Language Understanding Project
Demo - Creating a Knowledge Base : QnAMaker Tool Step-by-Step Guide
Demo - Knowledge Base Creation and Deployment with QnAMaker
Natural Language Processing (NLP) Solutions Overview
Analyze text & Process Speech - Knowledge Check
Translate Language & Language Understanding Model - Knowledge Check
Creating Conversational Q&A Solutions - Knowledge Check
Natural Language Processing (NLP) Solutions - Assessment
Knowledge Mining Solutions
Cognitive Search: Overview and Components
Exploring Search Components and Security Measures in Azure Cognitive Search
Exploring Multi-Turn Conversations and Context Management in Conversational Q&A Systems
Exploring Inbound and Outbound Traffic Security Measures in Azure Cognitive Search
AI Enrichment Skills Overview
Demo - Azure Cognitive Search Service: Configuring Alerts and Metrics
Demo - Diagnostic Settings and Scaling for Azure Cognitive Search Services
Demo - Using Application Insights for Azure Cognitive Search Monitoring
Demo - Creating a Cognitive Search Service
Demo - Cognitive Search - Indexing and Adding Cognitive Skills
Knowledge Mining Solutions Overview
Cognitive Search & AI Enrichment Skills - Knowledge Check
Knowledge Mining Solutions - Assessment
Conversational AI Solutions
Conversational Bot : Creating Bot - Frameworks and Conversational Flow
Connecting and Deploying a Conversational Bot
Conversational Bot : Deployment and Monitoring Best Practices
Conversational Bot : Activity Handlers, Dialogs or Topics, and Triggers
Conversational Bot : Adaptive Cards
Conversational Bot : Integration with Cognitive Services
Testing the Conversational Bot
Publishing the Conversational Bot
Demo - Bot Framework Setup : Console, SDK, and Emulator
Demo - Bot Framework Setup : Console, Configuration, and Azure Storage
How to Prepare for the Exam
Summary of AI-102
Key Takeaways
Conversational AI Solutions Overview
Course Conclusion
Build, Test and Publish Conversational Bot - Knowledge Check
Conversational AI Solutions - Assessment
Overall Assessment