[NEW] AWS Certified AI Practitioner

About this course

Detailed Exam Domain CoverageTo help you successfully pass the AWS Certified AI Practitioner certification, I have meticulously aligned this practice exam course with the official AWS exam guide. The questions you will encounter cover the following core domains:Fundamentals of AI and ML (20%)Understanding the differences between AI, ML, deep learning, and generative AI.Concepts of supervised, unsupervised, and reinforcement learning.Conceptual understanding of classification, regression, and clustering algorithms.The ML lifecycle: data collection, preparation, training, evaluation, deployment, and monitoring.Practical use cases: forecasting, recommendation, anomaly detection, computer vision, and NLP.Fundamentals of Generative AI (24%)Generative AI terminology and core concepts.Large language model (LLM) architectures and training methods.Use cases for text generation, image synthesis, and code assistance.Prompt engineering basics and advanced techniques.Model fine-tuning and evaluation metrics for generative outputs.Applications of Foundation Models (28%)Matching foundation model capabilities to business problems.Selecting the right AWS services (e.g., Amazon Bedrock, Amazon SageMaker).Evaluating performance and cost for foundation model inference.Implementing prompt techniques for various modalities.Assessing scalability and latency for production workloads.Guidelines for Responsible AI (14%)Fairness, bias detection, and mitigation strategies.Inclusivity and the importance of diverse training data.Transparency, explainability, and interpretability in AI models.