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
CourseFundamentalCompleted
Fundamentals of Analytics on AWS – Part 2
This course is the second of two offerings designed to introduce learners to the current market trends in analytics. Building upon the concepts introduced in Part 1, this course introduces learners to an overview of data lakes, data warehouses, and modern data architectures on AWS. You will learn about which AWS services can be used to build a data warehouse, data lakes, and modern data architectures on AWS. You will also see common modern data architecture use cases and a reference architecture. This course includes: lessons, videos, scenarios, and knowledge check questions.
AWS
CourseFundamentalCompleted
Amazon Connect Metrics and Analytics
In this course, you will discover how to use Amazon Connect metrics to make data-driven decisions. These insights improve the customer experience and operational efficiency. Whether you need to know how many contacts are waiting in queues. Or understand agent performance trends over time, the right metrics provide these critical insights. By the end of this training, you will be able to navigate both real-time and historical reports and create custom dashboards tailored to your specific needs. You will also help get the right information to the right people at the right time.
AWS
CourseFundamentalCompleted
Fundamentals of Analytics on AWS – Part 1
This course is the first of two offerings designed to introduce learners to the current market trends in analytics. In Part 1, you will learn fundamental concepts such as types of analytics, the 5 V's of big data, and the challenges associated with processing high volumes of data. This course also maps the 5 V's of big data to AWS services for analytics and discusses how AWS provides the most comprehensive services on the market. Following completion of this course, learners are encouraged to continue their journey with Fundamentals of Analytics on AWS - Part 2. Course level: Fundamental. Duration: 2 hours. This course includes: lessons, videos, scenarios, and knowledge check questions.
AWS
CourseAdvancedCompleted
Serverless Analytics
Customer data comes in all shapes and forms and from every direction. It's more critical than ever to connect and process all of that data, so that you can enable more data-driven decisions. In this course, Glenn Gillen will show you how to synthesize all of that disparate data using the power of tools like AWS IoT Analytics, Amazon Cognito, AWS Lambda, and Amazon SageMaker, to name a few. You will learn how to aggregate, process, store, and deliver actionable data in new and powerful ways.
AWS
CourseIntermediateCompleted
AI-DLC Foundations: Introduction
Introduction to the AI-Driven Development Lifecycle (AI-DLC), an AWS methodology for embedding AI agents and tools like Amazon Q Developer, Kiro, and Strands across software delivery. Covers core principles, AI-augmented roles, and how 'bolts' replace traditional sprints.
AWS
CourseFundamentalCompleted
Amazon Q Business Getting Started
Amazon Q Business is generative artificial intelligence (generative AI) powered assistant that can answer questions, generate content, create summaries, and complete tasks—all based on the information in your enterprise. In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and cost of using Amazon Q Business. You will also review an architecture that depicts how Amazon Q Business works. Through a guided tutorial consisting of a narrated video, step-by-step instructions, and transcript, you will learn how to create an Amazon Q web experience that uses a sample set of documents.
AWS
CourseIntermediateCompleted
AWS Panorama - Building Edge Computer Vision (CV) Applications
Overview of AWS Panorama for building computer vision applications that run on on-premises camera networks. Covers the appliance, application development workflow, model packaging, and deployment from the cloud to the edge.
AWS
CourseIntermediateCompleted
Building Retrieval Augmented Generation (RAG) workflows with Amazon OpenSearch Service
Demonstrates building retrieval-augmented generation workflows with Amazon OpenSearch Service as the vector store, including embedding ingestion, hybrid search, and integration with foundation models for grounded responses.
AWS
CourseFundamentalCompleted
Developing Machine Learning Solutions
In this machine learning course, you will learn about the machine learning lifecycle, and how to use AWS services at every stage. Additionally, you will discover the diverse sources for machine learning models and learn techniques to evaluate their performance. You will also understand the importance of machine learning operations (MLOps) in streamlining the development and deployment of your machine learning projects. This course includes interactive elements, text instruction, illustrative graphics and knowledge checks. Course level: Fundamental. Duration: 1 hour.
AWS
CourseFundamentalCompleted
Essentials of Prompt Engineering
Foundational prompt engineering course covering instruction design, few-shot examples, role and format prompts, and iterative refinement techniques applicable across modern foundation models.
AWS
Exam PrepFundamentalCompleted
Exam Prep Overview: AWS Certified AI Practitioner (AIF-C01 - English)
In this course, you will review the scope of the AWS Certified AI Practitioner (AIF-C01) exam, including the intended audience and exam topics.This course is part of 4 steps that you can use to prepare for your exam with confidence. To follow the 4 steps, enroll in the Exam Prep Plan: AWS Certified AI Practitioner (AIF-C01).The Exam Prep Plan includes exam-style questions, videos reviewing each exam domain and task statement, practice assessments, hands-on labs, flashcards, and more. The plan also includes role-based training to refresh your AWS knowledge and skills. Some of this content might require an AWS Skill Builder subscription.
AWS
CourseFundamentalCompleted
Exploring Artificial Intelligence Use Cases and Applications
In this course, you will explore real-world artificial intelligence (AI), machine learning (ML) and generative artificial intelligence (generative AI) use cases across a range of industries. These areas include healthcare, finance, marketing, entertainment, and more. You will also learn about AI, ML, and generative AI capabilities and limitations, model selection techniques, and key business metrics. This course includes interactive elements, videos, text instruction, and illustrative graphics.
AWS
CourseFundamentalCompleted
Fundamentals of Prompt Engineering with Claude
This course introduces learners to the foundational principles and best practices of prompt engineering, specifically tailored for using Anthropic’s Claude large language model (LLM) in the context of AWS. It provides a conceptual and practical starting point for AWS builders, technical professionals, and non-technical roles who want to effectively interact with Claude to solve business problems, build applications, or enhance productivity through natural language interfaces. The course emphasizes real-world AWS use cases where Claude can assist with infrastructure design, security reviews, documentation generation, troubleshooting, and customer support. By the end of this course you will be able to: Explain the basics of prompt engineering using Claude Recognize how Claude can support AWS cloud roles and tasks Write better prompts using specific structures and techniques Troubleshoot and iterate on prompts to improve results Use Claude responsibly with security and ethical best practices in mind
AWS
CourseFundamentalCompleted
Introduction to Amazon Nova Forge
Introduction to Amazon Nova Forge is a 100-level course designed for AI enthusiasts, Enterprise Architects, and Decision Makers to understand Amazon's service for building custom frontier models. Learn how Nova Forge enables organizations to develop specialized AI models using Nova checkpoints, blend proprietary data with Nova-curated training data, and host custom models on AWS. The course covers key benefits, training phases, and practical applications while maintaining IP control and cost-effectiveness. By the end of this course, you will be able to: Explain Amazon Nova Forge fundamentals and its benefits for custom frontier model development Understand how Nova Forge combines proprietary data with Nova-curated training data Identify and apply the four main training phases based on data volume and business needs Explore real-world use cases and success stories across industries Learn how Nova Forge addresses challenges in custom model development including catastrophic forgetting, IP control, and cost management
AWS
CourseFundamentalCompleted
Introduction to Amazon Q Developer (Technical)
In this course, you will learn about Amazon Q Developer and its role in software development lifecyle. You'll learn the platform's essential features, basic capabilities, and key benefits, giving you a solid foundation for understanding how this AI-powered tool can enhance your development workflow. By the end of this course, you'll have a clear grasp of what Amazon Q Developer offers and how it can benefit your software development.
AWS
CourseFundamentalCompleted
Introduction to Kiro powers
Kiro powers is specialized capabilities that give your AI agent the expertise it needs to work effectively with any tool or framework. Each Power packages two things: MCP(Model Context Protocol) server connections for tool access, and steering files with framework best practices. In this course, you will learn to understand what Kiro powers is and how it works, identify the key features and benefits of Kiro powers, and discover how to get started using it.
AWS
CourseIntermediateCompleted
Kiro: AI Development Best Practices
The course is designed for software engineers and operators who want to master Amazon Gen AI development skills. The course will introduce the Kiro family, including Kiro IDE, Kiro CLI, and Kiro Autonomous Agent. Additionally, it will provide an in-depth explanation of how to use Kiro to improve development efficiency and code quality. The course covers an overview of Kiro's core features, code generation and review techniques, and security best practices. Through a combination of theoretical studies and practical projects, master skills related to using Kiro to improve development efficiency, code quality, and security, and simplify project deployment and operation and maintenance.
AWS
CourseFundamentalCompleted
Model Context Protocol (MCP) – Simply explained
This course explores the fundamentals of Model Context Protocol (MCP) in a beginner-friendly way, taking you from foundational concepts to practical use cases. Through real-world applications Through clear explanations and real AWS examples, you'll understand what MCP is, how it works, and why it's useful. You will see demonstrations with AWS use cases that show MCP in action. Delivered by an expert instructor.
AWS
Exam PrepAdvancedCompleted
Official Practice Question Set: AWS Certified Generative AI Developer - Professional (AIP-C01 - English)
The Official Practice Question Set: AWS Certified Generative AI Developer - Professional (AIP-C01) consists of 20 questions. This question set aligns with the AIP-C01 version of the exam and exam guide. If you are looking for an assessment that is the same length as the AWS Certification exam, enroll in the Official Pretest or Official Practice Exam in the Exam Prep Plan. Official Practice Question Sets feature 20 questions developed by AWS to demonstrate the style of Certification exam questions. Each question includes detailed feedback for answer choices, including recommended resources to deepen your understanding of key topics. You can take the question set multiple times. Each time will include the same questions in a different order. This course is part of 4 steps that you can use to prepare for your exam with confidence. To follow the 4 steps, enroll in the Exam Prep Plan: AWS Certified Generative AI Developer - Professional (AIP-C01). Some of this content might require an AWS Skill Builder subscription.
AWS
Exam PrepFundamentalCompleted
Official Practice Question Set: AWS Certified AI Practitioner (AIF-C01 - English)
The Official Practice Question Set: AWS Certified AI Practitioner (AIF-C01) consists of 20 questions. This question set aligns with the AIF-C01 version of the exam and exam guide. If you are looking for an assessment that is the same length as the AWS Certification exam, enroll in the Official Pretest or Official Practice Exam in the Exam Prep Plan. Official Practice Question Sets feature 20 questions developed by AWS to demonstrate the style of Certification exam questions. Each question includes detailed feedback for answer choices, including recommended resources to deepen your understanding of key topics. You can take the question set multiple times. Each time will include the same questions in a different order. This course is part of 4 steps that you can use to prepare for your exam with confidence. To follow the 4 steps, enroll in the Exam Prep Plan: AWS Certified AI Practitioner (AIF-C01). Some of this content might require an AWS Skill Builder subscription.
AWS
CourseFundamentalCompleted
Optimizing Foundation Models
In this course, you will explore two techniques to improve the performance of a foundation model (FM): Retrieval Augmented Generation (RAG) and fine-tuning. You will learn about Amazon Web Services (AWS) services that help store embeddings with vector databases, the role of agents in multi-step tasks, define methods for fine-tuning an FM, how to prepare data for fine-tuning, and more. Course level: Fundamental. Duration: 1 hour. This course includes interactive elements, text instruction, and illustrative graphics.
AWS
CourseFundamentalCompleted
Responsible Artificial Intelligence Practices
In this course, you will learn about responsible AI practices. First, you will be introduced to what responsible AI is. You will learn how to define responsible AI, understand the challenges that responsible AI attempt to overcome and explore the core dimensions of responsible AI. Then, you will dive into some topics for developing responsible AI systems. You will be introduced to the services and tools that AWS offers to help you with responsible AI. You will also learn about responsible AI considerations for selecting a model and preparing data for your AI systems. Finally, you learn about transparent and explainable models. You will gain a solid understanding for what it means for a model to be transparent and explainable. You will also explore tradeoff considerations for transparent models and the principles of human-centered design for explainable AI. This course includes interactive elements, text instruction, illustrative graphics and knowledge checks.
AWS
CourseIntermediateCompleted
Accelerating generative AI development with fully managed MLflow 3.0 on Amazon SageMaker AI
In this course, you will learn how to accelerate generative AI development using fully managed MLflow 3.0 on Amazon SageMaker AI. You will explore how to track experiments, observe model behavior, and implement comprehensive tracing for generative AI applications.
AWS
CourseAdvancedCompleted
Advanced fine-tuning methods on Amazon SageMaker AI
In this course, you will learn advanced fine-tuning methods for large language models on Amazon SageMaker AI. This comprehensive training will guide you through the theoretical foundations and practical implementation of various fine-tuning approaches, helping you make optimal choices for your specific use cases, resource constraints, and business objectives.
AWS
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