By Data & AI Lab · Reviewed 14 September 2026
Week 1: AWS, AI and ML foundations
Learn cloud basics and distinguish AI, machine learning, deep learning, training and inference. Map classification, regression, forecasting and recommendation to practical use cases.
Week 2: The machine learning lifecycle
Study data preparation, feature concepts, model training, evaluation, deployment and monitoring. Learn when a managed AI service is more suitable than a custom model.
Week 3: Generative AI fundamentals
Learn foundation models, tokens, context, prompts, embeddings and common limitations. Practise explaining hallucination, bias and nondeterministic output.
Week 4: Amazon Bedrock and AWS AI services
Explore Bedrock model access and common managed services for language, vision, speech, search and documents. Focus on choosing a service from a business scenario.
Week 5: Foundation model applications
Study prompt patterns, retrieval-augmented generation, vector search, model evaluation, agents and guardrails at a conceptual level.
Week 6: Responsible AI, security and governance
Review fairness, transparency, explainability, privacy, least privilege, encryption, compliance, monitoring and human oversight.
Week 7: Apply and review
Complete small console exercises and explain each decision in your own words. Revisit the current exam guide and mark weak objectives.
Week 8: Assess readiness
Use official practice questions and an official practice assessment if available. Review incorrect answers by domain and schedule the exam only when results are consistently strong.
Open the interactive AIF-C01 roadmap
Frequently asked questions
Can I prepare for AIF-C01 in eight weeks?
Eight weeks is a reasonable planning example, but preparation time varies with prior AWS and AI experience.
Should I use exam dumps?
No. Use the official exam guide, legitimate training and practice questions. Dumps can be inaccurate and may violate exam rules.
Should I do hands-on labs?
Yes. Even though the exam is foundational, small exercises help connect service names and concepts to real decisions.