Microsoft Certified: AI Engineer Associate (AI-102)

Course Overview The Microsoft Certified: AI Engineer Associate (AI-102) course by Stalwart Learning is designed for professionals who want to build and deploy AI solutions using Microsoft Azure. This course…

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Stalwart Learning

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Date & Time

Price

Duration

5 Days / 40hrs

Location

https://stalwartlearning.com/

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Course Description

The Microsoft Certified: AI Engineer Associate (AI-102) course by Stalwart Learning is designed for professionals who want to build and deploy AI solutions using Microsoft Azure. This course provides an in-depth understanding of implementing machine learning models, natural language processing, computer vision, and conversational AI on the Azure platform. Participants will gain practical skills in designing, developing, and deploying AI-powered applications, preparing them for the AI-102 certification exam. By the end of the course, learners will be equipped to work with Azure Cognitive Services, Azure Machine Learning, and other Azure AI tools to create cutting-edge AI solutions.

40 hours (5 days)

  • Experience with Azure and cloud computing services.
  • Basic understanding of machine learning concepts and programming languages like Python or C#.
  • Familiarity with data engineering, including data preparation and transformation techniques.
  • Overview of Azure AI services and tools (Azure Cognitive Services, Azure Machine Learning)
  • Roles and responsibilities of an AI Engineer in an Azure environment
  • Identifying appropriate AI services based on solution requirements
  • Designing end-to-end AI solutions for business use cases
  • Integrating AI into existing systems
  • Using Azure Cognitive Services for image and video analysis (Computer Vision API, Face API)
  • Building custom vision models and training them for specific use cases
  • Implementing optical character recognition (OCR) and object detection
  • Leveraging Azure Cognitive Services for text analysis (Text Analytics API, Language Understanding (LUIS))
  • Implementing chatbots using Azure Bot Services
  • Working with sentiment analysis, entity recognition, and key phrase extraction
  • Designing conversational AI solutions with Azure Bot Framework
  • Integrating bots into web, mobile, and other applications
  • Leveraging QnA Maker and Dialogflow for building conversational interfaces
  • Using Azure Machine Learning Studio to build, train, and deploy machine learning models
  • Automating machine learning (AutoML) and hyperparameter tuning
  • Evaluating and improving model performance
  • Deploying AI models as APIs in Azure
  • Managing and monitoring deployed models with Azure Machine Learning and Application Insights
  • Ensuring scalability and performance for production-ready AI models
  • Implementing fairness and transparency in AI solutions
  • Ensuring data privacy, security, and compliance in AI models
  • Understanding and addressing bias in AI applications
  • AI-102 exam structure, study tips, and preparation strategies
  • Mock exams and scenario-based questions

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