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Foundational deep dive into Amazon Aurora, covering its distributed storage architecture, replication, failover behavior, performance characteristics, and the differences between Aurora Standard, I/O-Optimized, and Serverless v2 configurations.

Introduction to Amazon Aurora, AWS's MySQL- and PostgreSQL-compatible relational database engine. Covers cluster architecture, storage and replication design, performance characteristics, and how to provision and connect to an Aurora cluster.

Operational guide to Amazon EFS, covering performance and throughput modes, lifecycle management to Infrequent Access and Archive tiers, monitoring with CloudWatch, and cost optimization for shared file workloads.

Introduction to the AWS Snow Family, with a focus on AWS Snowball for petabyte-scale data transfer and edge compute. Covers ordering jobs, device handling, data encryption, and ingest into AWS storage services.

Technical deep dive into Amazon EBS performance, covering volume types (gp3, io2, st1, sc1), IOPS and throughput tuning, multi-attach, snapshots, and instrumenting workloads to identify and resolve storage bottlenecks.

Data modeling guidance for Amazon ElastiCache for Redis, covering key design, data type selection, expiration and eviction strategies, and patterns for caching, session storage, leaderboards, and pub/sub.

Design guidance for cloud-based content production workstations on AWS, covering remote workstations on EC2, NICE DCV streaming, storage tiers, and rendering and review pipelines for studios and post-production teams.

Foundational overview of Amazon Elastic Compute Cloud (EC2), covering instance types and families, AMIs, key pairs, security groups, and EBS storage. Designed for newcomers to AWS compute.

Hands-on introduction to launching and managing Amazon EC2 instances, including selecting an AMI, configuring networking and storage, connecting via SSH or RDP, and applying basic security best practices.

Introduction to running MariaDB on Amazon RDS, including instance and storage selection, parameter groups, backup and restore, multi-AZ deployments, and connecting from applications.

Conceptual primer on Amazon Relational Database Service, including supported engines, the shared responsibility model for managed databases, instance and storage architecture, and core operational features such as backups, snapshots, and Multi-AZ.

Hands-on lab using Amazon S3 Vectors as a vector store with Amazon Bedrock Knowledge Bases. Covers indexing embeddings in S3, configuring knowledge bases, and querying for retrieval-augmented generation use cases.

Architectural patterns for building cost-effective retrieval-augmented generation applications using Amazon Bedrock Knowledge Bases backed by Amazon S3 Vectors. Covers ingestion design, chunking strategies, and cost-versus-latency tradeoffs.

Beginner-friendly orientation to the AWS Cloud, covering core terminology, the AWS global infrastructure, common services across compute, storage, networking, and databases, and how to navigate the AWS Management Console.

Technical overview of foundational AWS services, including compute, storage, networking, databases, and security. Provides a working understanding of how core services fit together to host applications on AWS.
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