Design and deploy production-grade AI and ML architectures on AWS — from data ingestion to model inference at enterprise scale.
This advanced course is designed for solutions architects and engineers who need to design end-to-end AI/ML systems on AWS. Topics include data pipeline architecture with Kinesis, Glue, and Lake Formation, model training at scale with SageMaker, inference optimisation, MLOps practices, security for ML workloads, and integrating generative AI (Amazon Bedrock) into enterprise applications. Strong AWS experience recommended.
This course is designed for IT professionals, cloud engineers, developers, and business professionals seeking to build expertise in Amazon Web Services services. Whether you are starting your cloud journey or advancing toward a professional-level certification, our structured learning path and hands-on labs will prepare you thoroughly.
Basic IT literacy and familiarity with computing concepts is recommended. Specific technical prerequisites vary by level — Foundational courses have no prior experience requirement. Associate and Professional courses benefit from prior cloud exposure.