Join us for a FREE hands-on Meetup webinar on Text Analysis with Azure AI Language Service (AI102) | Friday, December 20th, 2024 · 5:00 PM IST/ 7:30 AM EST Join us for a FREE hands-on Meetup webinar on Text Analysis with Azure AI Language Service (AI102) | Friday, December 20th, 2024 · 5:00 PM IST/ 7:30 AM EST
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AI-102: Microsoft Azure AI Engineer

Build, Deploy, and Manage Intelligent Applications Using Azure AI Services

Duration

4 Days (8 hours per day)

Level

Intermediate Level

Design and Tailor this course

As per your team needs

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The AI-102 certification exam assesses your ability to design and implement AI solutions on the Azure platform. It evaluates your expertise in integrating AI capabilities into existing and new applications by leveraging Azure Cognitive Services, Azure Bot Service, and other Azure AI tools. Successful candidates will demonstrate the skills required to design, build, and operationalize end-to-end AI solutions that meet enterprise needs, ensuring scalability, security, and performance.



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  • AI Engineers: Professionals developing and deploying AI-based applications
  • Developers: Software developers integrating AI features into applications
  • Solution Architects: Architects responsible for designing AI-powered solutions
  • Data Scientists: Individuals looking to expand their knowledge in deploying AI solutions on Azure
  • IT Professionals: Engineers managing AI tools and solutions on cloud platforms
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  • Overview of Azure AI tools and services
  • Key AI concepts and their application in Azure
  • Introduction to Cognitive Services and AI deployment strategies
  • Working with Computer Vision
    • Image analysis
    • OCR (Optical Character Recognition)
    • Custom vision
  • Exploring Natural Language Processing (NLP)
    • Text Analytics
    • Translator
    • Speech recognition and synthesis
  • Decision-making APIs
    • Personalizer
    • Anomaly Detector
  • Creating chatbots with Azure Bot Service
  • Integrating bots with Cognitive Services
  • Advanced dialog design and language understanding (LUIS)
  • Securing and deploying conversational AI solutions
  • Building machine learning models with Azure Machine Learning
  • Training, validating, and deploying models
  • Using automated ML for custom scenarios
  • REST API integration and SDK usage
  • Deploying AI-powered microservices
  • Security and compliance considerations for AI solutions
  • Performance monitoring for AI solutions
  • Using Application Insights for diagnostic logging
  • Optimizing AI models for scalability and performance
  • Principles of responsible AI
  • Fairness, transparency, and explainability in AI solutions
  • Mitigating bias in AI models
  • Ensuring compliance with AI ethics and regulations
  • Deep dive into Language Understanding Intelligent Service (LUIS)
  • Integrating NLP models with conversational bots
  • Customizing language models with Azure OpenAI Service
  • Overview of Azure OpenAI Service
  • Using GPT models for text generation and summarization
  • Integrating OpenAI models into applications
  • Comprehensive review of all topics
  • Hands-on lab exercises and solutions
  • Mock exams with detailed explanations
  • Tips and strategies for success
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  • Familiarity with Azure platform fundamentals, including Azure Portal and basic cloud concepts
  • Proficiency in at least one programming language (e.g., Python, C#, or JavaScript)
  • Understanding of AI and ML principles, including concepts like supervised and unsupervised learning
  • Knowledge of API integration and HTTP protocols
  • Familiarity with data storage and database systems is recommended

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