Achievements
Certifications,
courses, and more
A live record of certifications, courses, training, and awards — pulled directly from the source of truth.
195
Achievements
3
Categories
249h 4m
Total Time
CourseIntermediateCompleted
Build with Amazon S3 Vectors and Amazon Bedrock Knowledge Bases
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.
AWS
CourseIntermediateCompleted
Building cost-effective RAG applications with Amazon Bedrock Knowledge Bases and Amazon S3 Vectors
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.
AWS
CourseAdvancedCompleted
Building Generative AI Applications Using Amazon Bedrock
End-to-end guide to building generative AI applications on Amazon Bedrock, including model selection, prompt design, knowledge bases, agents, guardrails, and integrating Bedrock with application back ends.
AWS
CourseFundamentalCompleted
Building Production-Ready Agents with TypeScript, Effect, and Amazon Bedrock
Walkthrough of building production-ready AI agents in TypeScript using the Effect library and Amazon Bedrock. Covers structured concurrency, error handling, and integrating tools and memory for reliable agent execution.
AWS
CourseAdvancedCompleted
Building Production-Ready AI Agents with Amazon Bedrock AgentCore
Practical guide to building production-grade agents on Amazon Bedrock AgentCore. Covers using the runtime, gateway, memory, identity, and observability primitives together to deploy reliable agents at scale.
AWS
CourseIntermediateCompleted
Building Safe and Responsible Generative AI Applications with Amazon Bedrock Guardrails
Covers using Amazon Bedrock Guardrails to apply content filters, denied topics, sensitive information redaction, and contextual grounding checks to keep generative AI applications safe, on-topic, and policy-aligned.
AWS
CourseFundamentalCompleted
Building with MultiModal Knowledge Bases in AWS Bedrock
Hands-on coverage of multimodal knowledge bases in Amazon Bedrock, where text, images, tables, and charts are ingested and queried together to ground generative responses in mixed-media corpora.
AWS
CourseIntermediateCompleted
Building Your Agentic Applications the Well-Architected Way
Guidance on applying the AWS Well-Architected Framework to agentic AI applications. Covers operational, security, reliability, performance, cost, and sustainability considerations specific to autonomous agent systems.
AWS
CourseIntermediateCompleted
Designing Secure Retrieval Augmented Generation (RAG) Applications with AWS
Security-focused guidance for designing RAG applications on AWS, covering data classification, access control on knowledge bases, prompt-injection mitigations, encryption, and auditing of LLM-generated outputs.
AWS
CourseIntermediateCompleted
Evaluate and Enhance RAG Performance with Amazon Bedrock
Covers evaluating and improving retrieval-augmented generation systems built on Amazon Bedrock, including retrieval and generation metrics, chunking and re-ranking strategies, and using Bedrock model evaluation tools.
AWS
CourseFundamentalCompleted
Exploring Amazon Nova models using Amazon Bedrock
Tour of the Amazon Nova family of foundation models on Amazon Bedrock, covering Nova Micro, Lite, Pro, and multimodal variants, their capabilities, and usage patterns for text, image, and video tasks.
AWS
CourseFundamentalCompleted
Fundamentals of Generative AI
Foundational course on generative AI concepts, including how foundation models, transformers, and diffusion models work, common use cases, customization options, and considerations for responsible deployment.
AWS
CourseFundamentalCompleted
Generative BI with Amazon Q in Quicksight - Getting Started
Amazon Q in QuickSight introduces a new suite of business intelligence (BI) capabilities by using the large language models (LLMs) of Amazon Bedrock and combining them with the capabilities of Amazon QuickSight. In this course, you will learn about technical concepts and the benefits of using Amazon Q in QuickSight. You will learn about the architecture of Amazon Q in QuickSight and how the built-in features help you to build dashboards and derive insights from your data with natural language queries. Course level: Fundamental. Duration: 60 minutes. This course includes presentations, demonstrations, and assessments.
AWS
CourseAdvancedCompleted
Increasing Application Security with Bedrock Guardrails and GenAI
Demonstrates using Amazon Bedrock Guardrails to harden GenAI-enabled applications, covering content filtering, denied topics, PII redaction, and contextual grounding checks for production-grade safety.
AWS
CourseAdvancedCompleted
Integrating Amazon Bedrock powered Agents with Model Context Protocol Servers using the Strands Agents SDK
Walkthrough of connecting Amazon Bedrock-powered agents to Model Context Protocol (MCP) servers using the Strands Agents SDK, enabling agents to access external tools and data sources via a standardized protocol.
AWS
CourseIntermediateCompleted
Introduction to Agentic AI on AWS
Conceptual introduction to agentic AI on AWS, covering what agents are, how they reason and use tools, and the AWS services that support building agents, including Amazon Bedrock Agents, AgentCore, and Strands.
AWS
CourseFundamentalCompleted
Introduction to Amazon Bedrock: Foundation Models and AI Applications
Introductory tour of Amazon Bedrock, covering available foundation models, the Bedrock playground, key APIs, and how to compose models with knowledge bases, agents, and guardrails to build AI applications.
AWS
CourseFundamentalCompleted
Introduction to Generative AI - Art of the Possible
Conceptual introduction to generative AI for business and technical audiences. Surveys common use cases across industries, the AWS generative AI stack, and considerations for selecting and deploying foundation models.
AWS
CourseFundamentalCompleted
Kiro Getting Started
Learn how to effectively use Kiro to write, debug, and maintain code while following best practices and team standards.
AWS
CourseIntermediateCompleted
Mastering Model Evaluation in Amazon Bedrock: From Basics to Best Practices
Comprehensive coverage of model evaluation in Amazon Bedrock, including automatic and human-in-the-loop evaluation jobs, choosing metrics, designing evaluation datasets, and operationalizing model selection.
AWS
CourseAdvancedCompleted
Prompt Engineering Best Practices for Amazon Bedrock Models
Practical prompt engineering best practices tailored to foundation models available on Amazon Bedrock, including model-specific prompt formats, system prompts, structured outputs, and techniques like chain-of-thought and self-consistency.
AWS
CourseIntermediateCompleted
Query Amazon Aurora PostgreSQL using Amazon Bedrock Knowledge Bases structured data
Demonstrates using Amazon Bedrock Knowledge Bases with structured data backed by Amazon Aurora PostgreSQL, enabling natural-language queries over relational data with grounded SQL generation and result synthesis.
AWS
CourseIntermediateCompleted
Spec-Driven Development with Kiro
This course introduces you to a new paradigm in the traditional AI-assisted software engineering approaches – Spec-Driven Development. In this course, you'll learn how to leverage Kiro, an AI-powered IDE, to revolutionize your development process through spec-driven development. You'll discover how to create comprehensive specifications before coding, leading to better alignment, improved documentation, and more efficient project management. By the end of this course, you'll be equipped with the skills to transform your development workflow, catch problems early, and build high-quality software with greater efficiency and control.
AWS
CourseAdvancedCompleted
Streamline GitHub workflows with generative AI using Amazon Bedrock and MCP
Demonstrates streamlining GitHub workflows using Amazon Bedrock and Model Context Protocol (MCP) servers, including generating pull request reviews, automating issue triage, and connecting agents to repository tools.
AWS
Want to work together?
I'm always learning and applying new skills — let's talk about how I can help on your next project.
Get in Touch