Fundamentals of AI and ML Literacy (Beginner Level)

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