aws-certified-ai-practitioner-brasil: an MIT-licensed PT-BR study track for AWS AIF-C01
Conteúdo em PT-BR para a AWS AI Practitioner (AIF-C01), com foco em fundamentos de IA/ML na AWS, serviços gerenciados (Bedrock, Sagemaker, etc.), boas práticas de governança e aplicações de negócio.
At a glance
- What is it?
- This repository is a Portuguese-language, HTML-based study path for the AWS Certified AI Practitioner exam, organised into 18 numbered modules from AI fundamentals through Amazon Bedrock, SageMaker, governance and mock questions. It is a content repository with a commercial funnel attached, not a tool you install.
- Who is it for?
- Adopt this if you are studying for AIF-C01 in Portuguese and want a numbered module index you can read in order, with the caveat that the repository is a content tree rather than a runnable project. Do not adopt it if you need English-language material, hands-on labs with working code, or a maintained question bank with published answer keys.
- Can I use it commercially?
- Yes. MIT is a permissive licence: you can use, modify and sell software built on it, as long as you keep its copyright and licence notices.
- Is it still maintained?
- Yes. The repository last received commits 6 days ago.
- What is it written in?
- Mainly HTML, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
The gap this repository addresses: AIF-C01 study material in Brazilian Portuguese
AWS certification preparation material is overwhelmingly published in English. For a Brazilian reader working through AIF-C01, the exam's vocabulary (foundation models, inference, guardrails, human review) has to be learned alongside the concepts themselves. This repository takes the position that the concepts should be presented in PT-BR first, with the service names kept in their original form. The README states the goal plainly: a base open source em PT-BR for AI fundamentals on AWS. The intended reader is someone starting from the beginning of the AIF-C01 scope, not someone already working with Bedrock or SageMaker daily. The repository's own framing is progressive reading, quick revision and guided practice, which is a study-workflow claim rather than a technical one. It is worth being clear about what this is: the primary language is HTML, and the deliverable is reading material plus a link out to a commercial platform, not a library, CLI or framework.
Module structure: 18 numbered directories under a single main branch
The repository layout is the product. The README lists 18 modules, each a directory with its own README.md, linked from a table. Modules 01 through 05 cover AI and ML introduction, generative AI fundamentals, machine learning fundamentals, foundation models and LLMs, and Amazon Bedrock. Modules 06 through 10 move into SageMaker, responsible AI and governance, data for AI, prompt engineering, and generative AI on AWS. Modules 11 through 15 handle security and compliance, use cases and architectures, AWS AI services, integration with applications, and best practices. Modules 16 through 18 are consolidation: mock exams and questions, a glossary, and a resources and links page. The roadmap section groups these into four study phases, which is a useful signal that the ordering is deliberate rather than alphabetical. Because every module is a directory with a README, the content is browsable on GitHub without cloning. There is no build step, no package manifest and no test suite described in the material.
What the README does not specify about module contents
The table tells you the topic of each module and nothing more. There is no indication of how many questions the simulados contain, whether answers are provided, whether the glossary is a flat term list or annotated, or whether the guided labs referenced in the overview table include commands to run. The overview mentions cheatsheets, flashcards and labs guiados as supporting material, but the module table does not map those artefacts to specific directories. If you are evaluating this for a study group, that is the first thing to check by opening 16-Simulados-e-Questoes and 17-Glossario directly on the main branch. The repository has no releases retrieved, so there is no versioned snapshot to pin your study plan to. Content lives on main and changes there. That is a normal arrangement for a study repository and also means there is no changelog to tell you what was revised between your first and second pass through a module.
Getting the material onto your machine: git clone and a browser
There is no install command in the supplied material, because there is nothing to install. The practical path is to clone the repository and read the markdown locally, or to browse it on GitHub. The clone command follows the standard GitHub pattern for the repository name:
git clone https://github.com/Thiago-code-lab/aws-certified-ai-practitioner-brasil.git
From there, the entry points named in the README are the module directories themselves, for example 05-Amazon-Bedrock/README.md or 16-Simulados-e-Questoes/README.md. The README also points to two sibling repositories for adjacent exams: aws-certified-cloud-practitioner-brasil for cloud fundamentals revision and aws-certified-solutions-architect-associate-brasil for architecture depth. Those cross-references are the only integration surface described. The assets directory holds the banner and logo images referenced at the top of the README, which is why the page renders as a branded landing page rather than a plain document.
The CloudStudy funnel is part of the repository, not a footnote
The README opens with a waitlist call to action for CloudStudy, links to the cloudstudy.com.br homepage, an Instagram account, a LinkedIn company page, a WhatsApp group and a Udemy course on data engineering on AWS. The homepage field on the repository points to cloudstudy.com.br. The licence is MIT, which permits reuse and modification of the content with attribution, but the README does not state which parts of the material are original and which are derived from AWS documentation or other sources. That matters if you intend to fork the content into your own course or internal training. MIT covers the repository's code and text as published; it does not grant rights over AWS's own documentation, service names or trademarks, and nothing in the README suggests the author has cleared or documented third-party provenance. This is not legal advice, and if you plan to redistribute the material commercially you should establish the provenance of each module yourself.
Where this is the wrong tool: hands-on practice and English-language study
AIF-C01 tests recognition of AWS services and their appropriate use, and the fastest way to build that recognition is to open the console and use the services. This repository, based on the material provided, is a reading and revision resource. The overview mentions labs guiados, but no lab instructions, IAM policies, CloudFormation templates or notebook files appear in the supplied README. If your study plan depends on running a Bedrock model invocation or training a SageMaker job, you will need a second source for the practical half. The second case is language. If your working environment is English, or if you will sit the exam in English, studying the concepts in PT-BR adds a translation step at exactly the moment you need recall speed. The repository's own README is written in Portuguese, so the material is monolingual by design. That is the point of the project, and it is also the boundary of its usefulness.
Alternatives and the actual difference in approach
The obvious comparison is AWS Skill Builder, which offers official AIF-C01 exam prep with practice questions and labs, in English, tied to the exam guide. The difference is not quality, it is provenance and language: Skill Builder is produced by the exam's owner and its practice questions are calibrated against the real question style, while this repository is an independent PT-BR synthesis whose question bank's size and fidelity are not stated in the README. A second comparison is the sibling repository aws-certified-cloud-practitioner-brasil by the same author, which covers the cloud fundamentals exam. If you are coming to AIF-C01 without a cloud background, the README itself points you there first, and that ordering is sensible because AIF-C01 assumes familiarity with core AWS concepts. A third option is simply reading the AWS service documentation for Bedrock, SageMaker and the managed AI services directly, which is more current than any study repository but gives you no study sequence. This repository's contribution is the sequence: modules 01 to 18 in a fixed order, with a consolidation phase at the end.
Maintenance cost and what to verify before committing study time
The last push recorded is 2026-09-09, and no releases were retrieved, so there is no tagged version to compare against. AWS renames services, changes console layouts and adjusts exam guides; a study repository that is not updated on that cadence will drift. The maintenance cost to you is low (git pull, re-read the changed module) but the risk is silent: nothing in the repository structure tells you which module is stale relative to the current AIF-C01 exam guide. Before you build a study schedule around it, check three things. First, open 16-Simulados-e-Questoes/README.md and confirm whether questions come with answers and explanations. Second, open 07-IA-Responsavel-e-Governanca/README.md and see whether governance content reflects the AWS services currently named in the exam guide. Third, confirm the module numbering in the table still matches the directory names on main, since the roadmap groups modules into phases that depend on that numbering holding. If those three checks pass, the repository is a reasonable PT-BR spine for AIF-C01 preparation, and you pair it with the AWS console for the practical half.
Editorial conclusion
Adopt this if you are studying for AIF-C01 in Portuguese and want a numbered module index you can read in order, with the caveat that the repository is a content tree rather than a runnable project. Do not adopt it if you need English-language material, hands-on labs with working code, or a maintained question bank with published answer keys. Before relying on it, open the module directories on the main branch and check whether 16-Simulados-e-Questoes contains actual questions with answers, and whether the roadmap's module numbering still matches the table.
Community notes