About AWS AI Practitioner (Beta) Exam

AWS recently announced two new certification exams, the AI Practitioner exam and the Machine Learning Engineer Associate exams, in addition to the existing Machine Learning Specialty certification. The AI Practitioner certification is an entry-level certification that can be attempted by individuals without in-depth technical knowledge of cloud concepts. The exam consists of 85 questions to be answered in 120 minutes, with a focus on theoretical knowledge rather than hands-on experience. To prepare for the exam, it is recommended to have a clear understanding of cloud computing basics, including the advantages and drawbacks of cloud vs on-prem, public vs private cloud, and pricing of cloud services. Additionally, surface-level knowledge of machine learning concepts and algorithms is required, including AI/machine learning, neural networks, deep learning, and generative AI. The exam also covers model training and evaluation, including model fit, bias, and variance, as well as metrics used to evaluate classification, regression, and large language models. Familiarity with AWS services for generative AI, such as AWS Bedrock, is also expected, including its features such as knowledge bases, agents, guardrails, and model evaluation. Prompt engineering is another topic covered in the exam, including useful prompting techniques that can yield better answers from a model. While hands-on experience is not required, it is recommended to do some meaningful preparation and consider enrolling in training provided by AWS or a third-party trainer. It is also important to note that this is not a comprehensive guide, and individuals seriously considering attempting this certification may want to enroll in training provided by AWS or a third-party trainer.