{"id":50423055,"url":"https://github.com/khasky/aws-ai-practitioner","last_synced_at":"2026-05-31T09:05:55.451Z","repository":{"id":346091781,"uuid":"1188476549","full_name":"khasky/aws-ai-practitioner","owner":"khasky","description":"Everything you need to know to become AWS AI Practitioner","archived":false,"fork":false,"pushed_at":"2026-03-22T06:11:25.000Z","size":19,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-03-22T21:12:39.719Z","etag":null,"topics":["ai","aif-c01","aws","exam","guide","practitioner","study"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/khasky.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-03-22T05:59:33.000Z","updated_at":"2026-03-22T06:11:27.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/khasky/aws-ai-practitioner","commit_stats":null,"previous_names":["khasky/aws-ai-practitioner"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/khasky/aws-ai-practitioner","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khasky%2Faws-ai-practitioner","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khasky%2Faws-ai-practitioner/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khasky%2Faws-ai-practitioner/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khasky%2Faws-ai-practitioner/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/khasky","download_url":"https://codeload.github.com/khasky/aws-ai-practitioner/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khasky%2Faws-ai-practitioner/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33725112,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-05-31T02:00:06.040Z","response_time":95,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","aif-c01","aws","exam","guide","practitioner","study"],"created_at":"2026-05-31T09:05:54.957Z","updated_at":"2026-05-31T09:05:55.434Z","avatar_url":"https://github.com/khasky.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Everything you need to know to become AWS AI Practitioner\n\nThis repo is a study guide for the **[AWS Certified AI Practitioner (AIF-C01)](https://aws.amazon.com/certification/certified-ai-practitioner/)** exam. It also covers how common AI and generative AI ideas show up on AWS in real projects.\n\nThe material follows the **official exam guide** ([PDF](https://docs.aws.amazon.com/pdfs/aws-certification/latest/ai-practitioner-01/ai-practitioner-01.pdf), [HTML hub](https://docs.aws.amazon.com/aws-certification/latest/ai-practitioner-01.html)). For exam scope, service names, and domain weights, rely on AWS docs and the guide; both can change.\n\n---\n\n## Who this is for\n\n- Professionals who need **foundational AI/ML and generative AI literacy** on AWS.\n- Candidates preparing for **AIF-C01** who want domain-by-domain coverage plus hands-on examples.\n- Anyone mapping **business problems** to the right AWS AI building blocks (without assuming you will train models from scratch).\n\nThe exam’s **target candidate** uses AI/ML on AWS but is **not** expected to implement deep model engineering, heavy MLOps pipelines, or organization-wide governance frameworks. On the exam those topics show up as _concepts_ to recognize, not as tasks to perform.\n\n---\n\n## Exam snapshot (official basics)\n\n| Item                 | Detail                                                            |\n| -------------------- | ----------------------------------------------------------------- |\n| **Exam code**        | AIF-C01                                                           |\n| **Level**            | Foundational (AWS Certification)                                  |\n| **Question types**   | Multiple choice, multiple response, ordering, matching            |\n| **Scored questions** | 50 (plus **15 unscored** questions that do not affect your score) |\n| **Passing score**    | **700** on a scaled score of 100–1000                             |\n| **Scoring model**    | Compensatory (overall pass; section weights differ)               |\n\n**Recommended knowledge (from AWS):** familiarity with core AWS services (for example EC2, S3, Lambda, **Amazon Bedrock**, **Amazon SageMaker AI**), the **shared responsibility model**, **IAM**, and **pricing models**. Up to about **six months**’ exposure to AI/ML on AWS is typical for the target candidate.\n\n**Out-of-scope job tasks (examples from AWS):** developing model algorithms, heavy feature engineering, hyperparameter tuning, building full AI/ML pipelines or security/compliance programs. On the exam you need to recognize _what_ these are, not perform them at expert depth.\n\n---\n\n## Content domains and weights (scored content)\n\n| Domain | Topic                                                 | Weight  |\n| ------ | ----------------------------------------------------- | ------- |\n| **1**  | Fundamentals of AI and ML                             | **20%** |\n| **2**  | Fundamentals of GenAI                                 | **24%** |\n| **3**  | Applications of Foundation Models                     | **28%** |\n| **4**  | Guidelines for Responsible AI                         | **14%** |\n| **5**  | Security, Compliance, and Governance for AI Solutions | **14%** |\n\n---\n\n## How to use this repo\n\n1. **Read the domain guides in order** (1 through 5). Later domains assume vocabulary from earlier ones.\n2. **Cross-link to AWS docs** for anything operational (IAM, encryption, regional availability, pricing).\n3. **Run the code examples** under `examples/` to connect API shapes to the concepts (Bedrock, boto3 patterns, evaluation and monitoring ideas).\n4. **Validate exam scope** using the official [in-scope services](https://docs.aws.amazon.com/aws-certification/latest/ai-practitioner-01/aif-01-in-scope-services.html) list.\n\n### Suggested study sequence (example)\n\n| Phase | Focus                  | Activities                                                                                  |\n| ----- | ---------------------- | ------------------------------------------------------------------------------------------- |\n| **1** | Vocabulary \u0026 lifecycle | Domain 1 guide; sketch one ML lifecycle for a business problem you know.                    |\n| **2** | GenAI building blocks  | Domain 2 guide; list 3 GenAI use cases and 2 failure modes (hallucination, cost).           |\n| **3** | FMs in production      | Domain 3 guide; practice explaining RAG, agents, and evaluation metrics out loud.           |\n| **4** | Responsibility \u0026 trust | Domain 4 guide; map tools (Guardrails, Clarify, Model Monitor, A2I) to risks.               |\n| **5** | Security \u0026 governance  | Domain 5 guide; trace IAM → encryption → logging for a Bedrock workload on paper.           |\n| **6** | Service mapping        | `guides/06-aws-services-primer.md`; drill “which service for which scenario?”               |\n| **7** | Hands-on               | Run Bedrock examples in a sandbox account; adjust inference parameters and observe changes. |\n\n---\n\n## Guide index\n\n| Guide                                       | File                                                                                             |\n| ------------------------------------------- | ------------------------------------------------------------------------------------------------ |\n| Domain 1: AI \u0026 ML fundamentals              | [guides/01-fundamentals-ai-and-ml.md](guides/01-fundamentals-ai-and-ml.md)                       |\n| Domain 2: Generative AI fundamentals        | [guides/02-fundamentals-of-genai.md](guides/02-fundamentals-of-genai.md)                         |\n| Domain 3: Foundation models in applications | [guides/03-applications-of-foundation-models.md](guides/03-applications-of-foundation-models.md) |\n| Domain 4: Responsible AI                    | [guides/04-responsible-ai.md](guides/04-responsible-ai.md)                                       |\n| Domain 5: Security, compliance, governance  | [guides/05-security-compliance-governance.md](guides/05-security-compliance-governance.md)       |\n| AWS services at a glance (exam-oriented)    | [guides/06-aws-services-primer.md](guides/06-aws-services-primer.md)                             |\n\n---\n\n## Code examples\n\n| Example                                                                  | Description                                                                           |\n| ------------------------------------------------------------------------ | ------------------------------------------------------------------------------------- |\n| [examples/bedrock_converse.py](examples/bedrock_converse.py)             | Invoke a foundation model with the **Converse** API (messages, inference parameters). |\n| [examples/bedrock_embeddings.py](examples/bedrock_embeddings.py)         | Generate **embeddings** for RAG-style workflows.                                      |\n| [examples/rag_similarity_concept.py](examples/rag_similarity_concept.py) | **Cosine similarity** between vectors (RAG retrieval concept).                        |\n| [examples/requirements.txt](examples/requirements.txt)                   | Minimal Python dependencies for the samples.                                          |\n\nExamples assume credentials via the default AWS credential chain (for example environment variables, `~/.aws/credentials`, or an IAM role). Replace model IDs and regions with values valid for your account.\n\n---\n\n## Official resources\n\n- [AWS Certified AI Practitioner](https://aws.amazon.com/certification/certified-ai-practitioner/) (certification home)\n- [Exam guide (AIF-C01)](https://docs.aws.amazon.com/aws-certification/latest/ai-practitioner-01.html) (domains, tasks, policies)\n- [Exam Prep on AWS Skill Builder](https://skillbuilder.aws/) (training aligned with AWS Certification)\n- [AWS Well-Architected](https://aws.amazon.com/architecture/well-architected/) (operational excellence, security, cost, sustainability)\n\n---\n\n## Disclaimer\n\nThis guide is **educational** and not affiliated with AWS. Exams, service names, and guides change; check AWS documentation before you schedule a test or design production systems.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkhasky%2Faws-ai-practitioner","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkhasky%2Faws-ai-practitioner","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkhasky%2Faws-ai-practitioner/lists"}