An industry-recognized credential shows employers and customers that a worker understands AI well enough to use it responsibly on the job. This instructor-led course prepares incumbent workers to earn the AWS Certified AI Practitioner (exam AIF-C01), a foundational certification for people who use, but do not necessarily build, AI and machine learning solutions. The course follows the five official exam domains: fundamentals of AI and ML, fundamentals of generative AI, applications of foundation models, guidelines for responsible AI, and security, compliance, and governance for AI solutions. Every topic is tied to an applied workplace scenario from a Massachusetts industry, so trainees learn the concepts by using them: choosing a model for a fictional insurer's claim summaries, designing a retrieval-grounded assistant for a manufacturer's SOPs, and assessing a healthcare chatbot for responsible-AI risks. Trainees complete guided hands-on labs in a provider-managed AWS sandbox with Amazon Bedrock and Amazon Q, timed practice exams, and cohort review sessions. Employers may instead select an alternate credential with the same hours and price: Google Cloud Certified Generative AI Leader or Microsoft Certified: AI Business Professional (AB-730). The per-slot price includes one exam voucher. The certification is issued by the vendor, not the provider.
What you will be able to do
By the end of the course, trainees will be able to:
- Explain core AI, ML, and generative AI concepts and terminology at the level tested in AIF-C01 Domains 1 and 2.
- Select an appropriate foundation model approach (prompting, retrieval-augmented generation, fine-tuning) for a given business scenario and justify the choice (Domain 3).
- Apply responsible AI guidelines, including bias, transparency, and human oversight, to a workplace case (Domain 4).
- Identify security, privacy, compliance, and governance controls for an AI solution, including the shared responsibility model (Domain 5).
- Achieve 80% or higher on two full-length timed practice exams before the scheduled certification attempt.
Who this course is for
IT support and systems administrators; Business and data analysts; Project and product managers; Sales engineers and technical account staff; Operations managers leading AI adoption; Compliance and risk staff
Before you start
Completion of FAST-01, FAST-02, or FAST-03, or equivalent experience using AI tools at work. AWS recommends up to 6 months of exposure to AI/ML on AWS; the sandbox labs supply that context. No coding required.
Hands-on activities
- Guided sandbox labs: prompt a foundation model in Amazon Bedrock; set up a knowledge-base grounded assistant over fictional SOPs; apply a guardrail; explore Amazon Q.
- Scenario clinics: cohort teams solve exam-style business scenarios drawn from MA industries and defend their answers.
- Domain checkpoints: short quizzes at the end of each session with instructor review of every missed item.
- Two full-length timed practice exams with personalized gap plans.
- Exam readiness session: test-taking strategy and scheduling.
How your learning is measured
- Attendance at all five sessions.
- Completion of all sandbox labs (instructor-verified).
- Domain checkpoint quizzes (75% to meet; reviewed if below).
- Two timed practice exams; 80%+ readiness standard.
- Course completion is attendance plus labs and practice exams; passing the vendor exam is tracked and reported as a credential outcome but is not a condition of course completion.
