Microsoft Certified Azure AI Engineer Associate AI-102

Requirements

• Fundamental Knowledge of Azure
• Programming Skills
• Data Science Concepts

Description

The Microsoft Certified: Azure AI Engineer Associate certification is designed for professionals who want to demonstrate their skills in building, managing, and deploying artificial intelligence (AI) solutions on the Microsoft Azure platform. The certification exam, Exam AI-102, covers a range of topics necessary for engineers working with Azure’s AI services.

Course Description:

This course prepares individuals for the Azure AI Engineer Associate exam by focusing on key Azure AI services and solutions. It covers designing AI solutions, integrating AI models, managing Azure AI services, and deploying AI applications at scale. The course is structured to help learners gain a deep understanding of core AI services such as machine learning, computer vision, natural language processing (NLP), and conversational AI.

Key Topics:

1. Planning and Managing Azure AI Solutions:

   • Design AI solutions using various Azure AI services such as Azure Cognitive Services and Azure Machine Learning.

   • Manage Azure AI resources and monitor solutions effectively.

2. Implementing Computer Vision Solutions:

   • Develop and integrate vision-based AI models, including image analysis, object detection, and facial recognition.

3. Implementing Natural Language Processing (NLP) Solutions:

   • Use tools like Azure Cognitive Services and Azure Machine Learning to process and analyze text, and implement chatbot solutions using the Azure Bot Service.

4. Implementing Conversational AI Solutions:

   • Develop AI models for creating chatbots and virtual assistants using Azure Bot Services and integrating NLP capabilities.

5. Deploying AI Models:

   • Deploy, monitor, and optimize AI models within Azure environments, ensuring that solutions are scalable and performant.

6. Maintaining AI Solutions:

   • Focus on monitoring AI models, retraining them as necessary, and maintaining system health post-deployment.

Learning Outcomes:

• Develop and deploy machine learning models using Azure services.

• Implement vision, speech, and language-based AI solutions.

• Manage AI resources and monitor their health.

• Use Azure Cognitive Services for pre-built AI models in applications.

• Design and deploy conversational AI bots for business scenarios.

Prerequisites:

While not mandatory, it’s recommended that candidates have foundational knowledge of:

• Programming skills (Python or C#)

• Basic understanding of cloud computing

• Some familiarity with data science and machine learning concepts.

For more detailed information on the course content and structure, you can visit Microsoft’s official page or other learning platforms offering related courses. This course is ideal for AI engineers aiming to specialize in cloud-based AI solutions using Microsoft Azure.

Who this course is for:

• EVERYONE