Daily Archives: January 19, 2025

Mastering Generative AI and Machine Learning on Azure: Top Questions for Self-Upskilling

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Here are 20 questions to test your understanding and application after completing the “AI Career Advancement: Comprehensive Training in Generative AI and Machine Learning on Azure” course:

https://classplusapp.com/w/wlp/kqegdo/course-kqegdo-1737287364726

  1. How do you configure and deploy a machine learning model using Azure Machine Learning Studio?
  2. What are the key components of Azure Cognitive Services, and how can they be utilized in a real-world application?
  3. Explain the process of implementing Natural Language Processing (NLP) using Azure services.
  4. How do you set up and manage Azure Cognitive Search for an AI-based project?
  5. Describe the steps involved in developing a conversational AI solution using Azure Bot Service.
  6. What is MLOps, and how does it integrate with Azure Machine Learning for operationalizing machine learning models?
  7. How can you leverage Azure Computer Vision for image recognition tasks?
  8. What are the benefits of using transfer learning in generative AI models, and how can it be applied in Azure?
  9. How do you implement speech recognition and synthesis using Azure Speech Services?
  10. What are the best practices for securing Azure AI services and data?
  11. How can you use Azure Knowledge Mining to extract insights from unstructured data?
  12. Describe a scenario where you would use Azure Blob Storage in conjunction with machine learning.
  13. What are the key differences between AI, machine learning, and generative AI?
  14. How do you handle version control and continuous integration in an Azure MLOps pipeline?
  15. Explain the concept of object detection and how it can be implemented using Azure Computer Vision.
  16. How can you create and deploy a predictive analytics solution using Azure Machine Learning and Power BI?
  17. What is the role of Azure Container Instances in deploying machine learning models?
  18. How do you integrate Azure Cognitive Services with a web application to enhance user experience?
  19. What are the key considerations for optimizing the performance of AI models on Azure?
  20. How can you use Azure DevOps to manage and deploy machine learning projects?

These questions will help you assess your knowledge and practical skills gained from the course, ensuring you are well-prepared for real-world applications and interviews.

https://www.linkedin.com/pulse/ai-career-advancement-comprehensive-training-machine-mgddc