SKILL BENCHMARK

AI Landscape Literacy (Beginner Level)

  • 18m
  • 18 questions
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The AI Landscape Literacy (Beginner Level) benchmark measures your ability to recall and recognize the fundamentals of artificial intelligence (AI) and machine learning (ML). You will be evaluated on your knowledge of how algorithms learn and perform common tasks like classification and clustering and the importance of deep learning models. A learner who scores high on this benchmark demonstrates that they have the basic foundational knowledge of AI.

Topics covered

  • compare supervised and unsupervised learning techniques
  • explain how convolutional neural networks (CNNs) work
  • explain how recurrent neural networks (RNNs) work
  • outline how classification models work and how they can be evaluated
  • outline how clustering models work and how they can be evaluated
  • outline how deep learning models work
  • outline how ensemble techniques are implemented
  • outline how neural network models can be trained
  • outline how regression models work and how they can be evaluated
  • outline how reinforcement learning algorithms work
  • outline important milestones in artificial intelligence over the last few decades
  • outline the use of attention-based models
  • provide an overview of how machine learning works
  • recognize how generative adversarial networks (GANs) are implemented
  • recognize how text data is fed into neural networks
  • recognize the algorithmic structure of linear regression, logistic regression, and decision tree models
  • recognize the nuances in defining artificial intelligence (AI) and machine learning (ML)
  • summarize how neurons transform inputs