[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"cheat-sheet---en":3,"domain-info---en":3,"topic-info----en":3,"prev-aws-certified-ai-practitioner-ai-ml-fundamentals-ai-ml-core-concepts-supervised-unsupervised-reinforcement-en":4,"next-aws-certified-ai-practitioner-ai-ml-fundamentals-ai-ml-core-concepts-supervised-unsupervised-reinforcement-en":18,"lesson-aws-certified-ai-practitioner-ai-ml-fundamentals-ai-ml-core-concepts-supervised-unsupervised-reinforcement-en":27},null,{"locked":5,"reason":6,"meta":7,"item":3},true,"paywall",{"title":8,"description":9,"isFree":10,"estimatedMinutes":11,"difficulty":12,"learningObjectives":13},"Types of Data in AI","Learn the two independent properties of AI data, structure and labeling, and how tabular, time-series, image, and text formats map to real machine learning problems.",false,15,"beginner",[14,15,16,17],"Distinguish structured, semi-structured, and unstructured data","Distinguish labeled from unlabeled data and connect each to a learning type","Explain why structure and labeling are independent properties of a dataset","Identify tabular, time-series, image, and text data and their typical uses",{"locked":5,"reason":6,"meta":19,"item":3},{"title":20,"description":21,"isFree":10,"estimatedMinutes":11,"difficulty":12,"learningObjectives":22},"Types of Inferencing","Once a model is trained, inference is how it serves predictions. Compare real-time, batch, asynchronous, and serverless inference and match each to latency, payload, and traffic needs.",[23,24,25,26],"Define inference and distinguish it from training","Compare real-time, batch, asynchronous, and serverless inference","Match an inference type to latency, payload, and traffic requirements","Map the inference types to Amazon SageMaker options",{"locked":5,"reason":6,"meta":28,"item":3},{"title":29,"description":30,"isFree":10,"estimatedMinutes":31,"difficulty":12,"learningObjectives":32},"Supervised, Unsupervised, and Reinforcement Learning","The three ways a model can learn: supervised learning from labeled examples, unsupervised learning from unlabeled data, and reinforcement learning from reward and penalty.",16,[33,34,35,36],"Explain supervised learning and its two main tasks, regression and classification","Explain unsupervised learning and the clustering task","Explain reinforcement learning through the agent, environment, and reward loop","Match a problem to the right learning type based on the data available"]