CBSE Class 8 · Artificial Intelligence · 2026-27

AI Project Lifecycle: Worksheet

Skills: Algorithmic thinking, Decomposition. Circle the correct answer. Show your working in the space beside each question.

  1. What is the first stage of the AI project lifecycle?
    • (a) Problem scoping
    • (b) Modelling
    • (c) Evaluation
    • (d) Deployment
  2. Which order of stages is correct?
    • (a) Problem scoping → Data acquisition → Data exploration → Modelling → Evaluation
    • (b) Modelling → Problem scoping → Evaluation → Data acquisition → Data exploration
    • (c) Evaluation → Modelling → Data acquisition → Problem scoping → Data exploration
    • (d) Data exploration → Evaluation → Problem scoping → Modelling → Data acquisition
  3. Students collect photos of healthy and diseased leaves for their project. Which stage is this?
    • (a) Data acquisition
    • (b) Evaluation
    • (c) Problem scoping
    • (d) Deployment
  4. Students make charts to check how many photos they have of each disease and find blurry images. Which stage is this?
    • (a) Data exploration
    • (b) Modelling
    • (c) Deployment
    • (d) Problem scoping
  5. Why must a model be evaluated on data it did not see during training?
    • (a) A model can memorise its training data and still fail on new examples
    • (b) Training data is always wrong
    • (c) New data makes the model faster
    • (d) Evaluation is not needed
  6. The 4Ws problem canvas used in problem scoping asks which four questions?
    • (a) Who, What, Where, Why
    • (b) When, Which, Whose, Whom
    • (c) Who, When, How, How much
    • (d) What, Which, While, Why

Answer key: AI Project Lifecycle

  1. (a) Problem scoping – Every later stage depends on it.
  2. (a) Problem scoping → Data acquisition → Data exploration → Modelling → Evaluation – Finally evaluate it, and loop back if needed.
  3. (a) Data acquisition – So this is data acquisition.
  4. (a) Data exploration – Finding problems now saves a poor model later.
  5. (a) A model can memorise its training data and still fail on new examples – That is why evaluation uses a separate test set.
  6. (a) Who, What, Where, Why – Why: the benefit of solving it.