Exam Prep AI-102: Microsoft Azure AI Engineer Associate

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Exam Prep AI-102: Microsoft Azure AI Engineer Associate

Coursera · Intermediate ·🛡️ AI Safety & Ethics ·1mo ago
The AI-102: Designing and Implementing a Microsoft Azure AI Solution certification exam tests the candidate’s 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: Con
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