Fundamentals of AI and ML Literacy (Beginner Level)

  • 12m
  • 12 questions
The Fundamentals of AI and ML Literacy (Beginner Level) benchmark measures your knowledge of the foundational concepts of data science, artificial intelligence (AI), and machine learning (ML). You will be evaluated on your ability to recognize use cases of AI and ML and outline foundational and advanced data science methods. A learner who scores high on this benchmark demonstrates that they have a basic understanding of AI and ML.

Topics covered

  • describe the concept of and use cases for text mining
  • describe the role of NLP in text analysis and language understanding and identify NLP use cases
  • identify concepts and use cases for AI
  • identify the concept of and use cases for neural networks, including the working principles of neural networks and deep learning models
  • identify the uses of classification and name common classifiers
  • identify use cases for AI and describe how AI can be used in your industry
  • identify use cases for machine learning, differentiate between supervised and unsupervised machine learning, and identify use cases for supervised and unsupervised machine learning
  • name use cases for simple linear regression
  • outline clustering and differentiate its benefits and challenges
  • outline regression, its benefits, and challenges
  • outline the process of feature engineering and its impact on model performance
  • recognize concepts of anomaly detection, identify anomaly detection use cases, and describe the importance of anomaly detection and outlier analysis in artificial intelligence (AI) applications