Video summary

AI 900 Exam Q&A #1 - Azure AI Fundamentals

Main summary

Key takeaways

Educational

Video overview / logistics

  • Presenter: Bibek
  • Content: 250 questions and answers for AI-900 (Azure AI Fundamentals)

  • Exam info:

    Passing score = 700 / 1000. Fee varies by country (presenter mentions £69 in the UK).

  • Download / purchase: Bibek offers the full question set on his “Buy Me a Coffee” page; members get 50% off.

Main topics covered (questions 1–10)

  • Purpose and scope of conversational AI
  • Basic dataset handling for model training and evaluation
  • Microsoft guiding principles for responsible AI (accountability; reliability & safety; privacy & security)
  • Choosing the correct Azure resource for a given AI task (Form Recognizer for receipts)
  • NLP tasks for monitoring news (entity recognition and sentiment analysis)
  • Distinguishing classification use cases from regression/clustering tasks
  • Azure OpenAI models and primary capabilities (DALL·E for image generation)
  • Basic ML workflow step ordering (load data first)
  • Responsible AI considerations for handling unusual/missing values (reliability & safety)
  • Possible channels a bot can connect to (Teams, email, web chat, Alexa)

Detailed Q&A (questions 1–10)

  1. Detecting a change in hospital infection rates is a scenario of conversational AI.

    • Correct answer: False

  2. You are testing a machine learning model — how should you split data for training and evaluation?

    • Options:
      • A: features for training / labels for evaluation
      • B: randomly split rows into training and remaining rows for evaluation
      • C: labels for training / features for evaluation
      • D: split columns
    • Correct answer: B — randomly split the data (rows) into training and evaluation sets

  3. Drag-and-drop: Microsoft guiding principles for responsible AI — match descriptions to principles.

    • “Implementing processes so that decisions made by the AI system can be overridden by humans” → Accountability
    • “Ensure AI systems operate as designed, respond to unanticipated conditions and resist harmful manipulations” → Reliability and safety
    • “Provide consumers with information and controls over the collection, use, and storage of their data” → Privacy and security

  4. Team member plans to use the Form Recognizer pre-built receipt model — which Azure resource should you recommend?

    • Options: Face service; Form Recognizer; Computer Vision
    • Correct answer: Form Recognizer

  5. System to scan news for articles about customers, alert on negative articles, add positive articles to a press book — which NLP tasks to use?

    • Correct answers: Entity recognition (to find customer mentions) and Sentiment analysis (to classify articles as negative/positive)

  6. Select the correct use case for classification.

    • Options included:
      • Predict number of cups of coffee (regression)
      • Predict minutes to run a race (regression)
      • Predict whether someone uses a bicycle to travel to work based on distance (classification)
      • Group images by color (clustering)
    • Correct answer: Predicting whether someone uses a bicycle to travel to work based on distance from home to work (classification)

  7. Which Azure OpenAI model can generate original images from natural language?

    • Options: DALL·E; Whisper; Embeddings; GPT-3.5; GPT-4
    • Correct answer: DALL·E

  8. You have a dataset and need to build an Azure ML classification model to identify defective products — what should you do first?

    • Options: create a clustering model; split data into training/testing; create a classification model; load the dataset
    • Correct answer: Load the dataset

  9. Developing an AI system that will be ingesting unusual and missing values — which Microsoft responsible AI principle applies?

    • Options: Inclusiveness; Reliability and safety; Fairness
    • Correct answer: Reliability and safety

  10. What channels can a bot be connected to? (select all correct) - Correct answers: Microsoft Teams; Email; Web chat; Alexa

Speakers / sources identified

  • Bibek (presenter)

Original video