How I Passed the AWS Certified AI Practitioner Exam

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On June 6, 2025, I passed the AWS Certified AI Practitioner (AIF-C01) exam with a score of 885 out of 1000. This certification marks my entry into the field of cloud-based artificial intelligence and machine learning, and in this post I’ll share my complete journey — from study materials and hands-on labs to dealing with technical hurdles during the exam.

Why I Took This Certification

With AI transforming industries rapidly, I wanted to gain both theoretical understanding and practical experience with AWS AI/ML services. This certification was ideal for establishing foundational knowledge while validating my ability to apply AI responsibly within the AWS ecosystem.

My Study Approach

1. AWS Skill Builder — Structured Learning

I started with the official AWS Skill Builder course. It covers all five domains of the exam:

  • Domain 1: Fundamentals of AI and ML (20% of scored content)
  • Domain 2: Fundamentals of Generative AI (24%)
  • Domain 3: Applications of Foundation Models (28%)
  • Domain 4: Guidelines for Responsible AI (14%)
  • Domain 5: Security, Compliance, and Governance for AI Solutions (14%)

I created a comprehensive study document by following each video and caption. This became my centralized notes with a domain-by-domain overview of all topics.

2. Stéphane Maarek’s Udemy Course

I then followed the Ultimate AWS Certified AI Practitioner AIF-C01 course on Udemy by Stéphane Maarek. The lessons were clear and hands-on. I especially appreciated the deep dive into real-world use cases, and reviewed the slide decks repeatedly to reinforce the core services and their ideal use cases.

3. Hands-On Labs (freeCodeCamp)

To go beyond theory, I practiced with Andrew Brown’s free YouTube course, which focuses on hands-on AWS experience. Here’s what I practiced and learned:

  • Amazon SageMaker — Creating Jupyter notebooks, training and deploying ML models.
  • Amazon Bedrock — Integrating foundation models from providers like Anthropic and AI21 Labs for generative AI use cases.
  • Amazon Forecast — Using time-series data to build predictive models.
  • Amazon Kendra — Implementing intelligent search functionality.
  • Amazon Textract — Extracting structured data from documents (e.g., invoices, forms).

Practice Tests and Review

I completed 20 free and 65 paid questions from AWS Skill Builder, plus all 4 sets of Stéphane Maarek’s practice tests on Udemy. I didn’t just answer questions — I analyzed each incorrect answer and reviewed the concepts behind every distractor. This review cycle helped reinforce weak areas.

My Exam Day: Real-World Hurdles

Originally, I scheduled the exam for May 30, 2025, but Pearson VUE’s software failed to launch on my office laptop. I rescheduled to June 6, before Eid-al-Adha, using my personal laptop — and this time the proctoring setup worked smoothly. The format included single- and multiple-choice questions, case studies, and match-type questions (matching services to their use cases). The questions were more conceptual and real-world-focused than the practice sets, but my hands-on experience helped me reason through them confidently.

Final Thoughts & Tips

  • Start with official AWS Skill Builder — it gives a clear roadmap.
  • Review your notes regularly — creating your own summary boosts retention.
  • Get hands-on with as many services as possible — understand when and why to use each.
  • Don’t rely on memorization — focus on use cases and architectures.
  • Stay calm during the exam — even if questions look unfamiliar, reason through them using your understanding of the services.

If you’re on your way to becoming AWS Certified, I’d be happy to share my study doc or help you plan your prep. Let’s build responsibly with AI! You can view my earned badge on Credly.

This article was also published on Medium.