A practical study guide for AIF-C01 Domain 5: IAM, encryption, network isolation, AI-specific attack vectors, compliance frameworks, data governance, and the GenAI Security Scoping Matrix.

Domain 4 of the AWS AI Practitioner exam covers Responsible AI (14%). This guide covers the six responsible AI dimensions, SageMaker Clarify bias metrics, Bedrock Guardrails, model transparency tools, and RLHF.

Key design considerations for FM-based applications on AWS: model selection, RAG, inference parameters, Agents for Amazon Bedrock, and customization tradeoffs. Covers Domain 3 of the AIF-C01 exam.

A breakdown of the AWS generative AI stack, key services like Bedrock and SageMaker JumpStart, pricing models, and the security fundamentals tested on the AIF-C01 exam.

A breakdown of generative AI fundamentals for the AIF-C01 exam: transformers, embeddings, diffusion models, the foundation model lifecycle, and AWS services.

A practical breakdown of what generative AI can and cannot do for business, covering capabilities, core limitations, RLHF, hallucinations, evaluation metrics, and KPIs for the AWS AIF-C01 exam.

A complete walkthrough of the ML development lifecycle for the AWS AI Practitioner exam (AIF-C01): five phases from business goal to monitoring, AWS SageMaker services mapped to each step, and every evaluation metric with formulas and use cases.

Task Statement 1.2 of the AIF-C01 exam: when to use AI vs rule-based systems, ML problem types (classification, regression, clustering, anomaly detection), AWS pre-trained services, and real-world case studies.

Task Statement 1.1 of the AIF-C01 exam covers AI fundamentals: the AI/ML/deep learning hierarchy, training data types, inference options, learning styles, model quality problems, and generative AI.

A practical breakdown of the AWS AI Practitioner (AIF-C01) exam: domain weightings, all five question types with strategies, the 4-step prep methodology, and registration options.

A developer's guide to prompt anatomy, inference parameters, core techniques (zero-shot, few-shot, chain-of-thought), and security risks like prompt injection and jailbreaking.

A developer's guide to security, compliance, and governance for AI systems on AWS. Covers defense in depth, the Shared Responsibility Model, OWASP Top 10 for LLMs, the GenAI Security Scoping Matrix, and secure data engineering.

A breakdown of the 5-stage generative AI application lifecycle on AWS: from defining a use case and selecting a foundation model to improving performance, evaluating results, and deploying with monitoring.

The ML development lifecycle follows the same build-test-deploy-monitor loop developers already know, but models degrade over time as data shifts. Here's what makes it different.

Foundation models are powerful out of the box, but closing the gap between general training data and your specific use case requires either RAG or fine-tuning. Here's how each works and when to use them.

Responsible AI is not a compliance checkbox. It shapes your architecture, model selection, and dataset prep from day one. Here is what stood out from studying AWS's Responsible AI course.

Not every problem needs ML. A breakdown of real-world AI use cases, the three core ML techniques, generative AI challenges, and how to pick the right model.

Learn to install AWS CDK on your AWS account. This guide covers installation, verifying with cdk --version, bootstrapping your environment, and troubleshooting permissions for smooth CDK application deployment.

Learn how to install and configure AWS CLI v2 on macOS. This guide covers downloading, installation, verifying the version, and setting up config and credentials files, ensuring a smooth setup for managing AWS services directly from your terminal.

Setup Mixpanel in a NextJS app

Learn to install and configure Cypress and Jest in a NextJS with typescript. Avoid typescript errors.

Learn how to deploy the storybook to Vercel and learn how to read an environment variable from storybook

Render subcomponents inside a parent component Storybook story

Use NextJS dynamic feature to dynamically import components at build time

Add a blog to your existing NextJS app with Contentful

Clean and format your code automatically with Prettier, lint-staged and Typescript