Agent Knowledge Bases and Memory
Design persistent memory and knowledge systems for AI agents. Covers short-term and long-term memory, vector stores and embeddings, RAG architectures, knowledge base integration, and advanced retrieval strategies.
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Design persistent memory and knowledge systems for AI agents. Covers short-term and long-term memory, vector stores and embeddings, RAG architectures, knowledge base integration, and advanced retrieval strategies.
Learn AI-assisted software development with agents. Master agent architecture, skills, context management, pipelines, OpenCode workflows, and best practices for the future of coding.
Learn algorithmic thinking without code. Master pseudocode, logic structures, quality principles, and design algorithms through conceptual examples and real-world analogies.
Comprehensive preparation for the AWS Certified AI Practitioner (AIF-C01) exam covering AI/ML foundations, generative AI on AWS, building and operating solutions with Amazon Bedrock and SageMaker, security, cost optimization, and responsible AI, with architecture diagrams, real case studies, and exam-style practice questions.
Comprehensive preparation for the AWS Certified Cloud Practitioner (CLF-C02) exam covering cloud concepts and economics, security and compliance, AWS global infrastructure and core services, and billing, pricing, and support, with architecture diagrams, real AWS customer case studies, and exam-style practice questions including multiple-response drills.
End-to-end architecture and implementation course for a production AWS data lakehouse, S3 storage tiers including Glacier, open table formats (Iceberg/Hudi/Delta), Glue Data Catalog and ETL, Athena and Redshift query layers, streaming and batch ingestion, Lake Formation governance with row/column-level security, Macie-driven PII protection, orchestration, data quality, cost optimization, and QuickSight BI, with architecture diagrams, real AWS customer cases, worked pricing examples, and practice questions.
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