# AI Practitioner Certification Prep: AWS Certified AI Practitioner (with employer-selected alternate exam)

**Course FAST-12** · 20 hours · Instructor: Wadood Chaudhary · Presented by 7formations

## Session 1. AI and ML fundamentals (Domain 1) (4 hours)

- Exam overview and study plan
- AI vs ML vs deep learning; supervised and unsupervised
- ML lifecycle and metrics, in business terms
- When AI is not the answer
- **Lab 1: Sandbox orientation; Domain 1 checkpoint.**

## Session 2. Generative AI fundamentals (Domain 2) (4 hours)

- Tokens, embeddings, foundation models
- Capabilities and limits; cost drivers
- Bedrock model playground
- **Lab 2: Prompt and compare models on a fictional claim summary; Domain 2 checkpoint.**

## Session 3. Applications of foundation models (Domain 3) (4 hours)

- Prompt engineering techniques
- Retrieval-augmented generation
- Fine-tuning vs prompting; evaluation
- Agents, in concept
- **Lab 3: Knowledge-base assistant over fictional Bayside SOPs; Domain 3 checkpoint.**

## Session 4. Responsible AI, security, and governance (Domains 4 and 5) (4 hours)

- Bias, fairness, transparency, explainability
- Guardrails and human review
- Shared responsibility, IAM, encryption, data governance
- Compliance frameworks
- **Lab 4: Apply a guardrail; responsible-AI case on a fictional clinic chatbot; Domains 4-5 checkpoint.**

## Session 5. Exam readiness (4 hours)

- Practice exam 1 review
- Practice exam 2 (timed)
- Gap plans and exam scheduling
- **Lab 5: Practice exams and personal gap plan.**

## Worksheets and deliverables

- W1 Personal study plan
- W2-W5 Lab completion sheets
- W6 Domain checkpoint results
- W7 Practice exam gap plan

## Attendance and completion

- Attendance is recorded at the start and end of every session (live virtual: platform attendance log plus an instructor roll call or poll; in-person: signed sheet).
- A trainee must attend 100% of instructional hours. A missed session may be made up by attending the same session in another scheduled cohort within 30 days; the make-up is logged the same way.
- A trainee must submit every required lab deliverable and score 'Meets' on the final applied task.
- Each completion record is tied to the trainee, the employer FEIN, and the course number, and is kept for the contract retention period.
- Incomplete trainees are not reported as completions and are not billed to anyone. FAST AI pays for completions only; employers and trainees are never charged.
- Optional asynchronous pre-work (under 10% of course time) is supplemental, is not counted as instructional hours, and never substitutes for a live session.

## Assessment rubric

Each criterion is scored Not yet / Meets / Strong. Completion requires Meets on every criterion for the final deliverable (resubmission allowed within the course window).

| Criterion | Meets standard |
| --- | --- |
| Domain mastery | 75%+ on each domain checkpoint |
| Applied scenarios | Correct approach chosen and justified in clinics |
| Labs | All sandbox labs completed and verified |
| Exam readiness | 80%+ on practice exams |