AWS AI Practitioner Exam: My Experience, Study Plan, and Resources

AWS AI Practitioner Exam: My Experience, Study Plan, and Resources


The AWS Certified Artificial Intelligence Practitioner exam, currently in its beta phase, is designed for individuals eager to demonstrate their understanding of AI and machine learning concepts using AWS services. I recently took this beta exam to test my knowledge and contribute to the shaping of its final version. My motivation stemmed from a desire to stay ahead in the ever-evolving field of AI and enhance my career prospects in cloud-based AI solutions. In this article, I’ll share my experience with the beta exam, outline the preparation strategies that worked for me, and discuss the resources I found most beneficial. If you’re considering taking this exam or are curious about it, read on for valuable insights and tips!

The AWS Certified AI Practitioner exam is designed to validate foundational knowledge of artificial intelligence (AI), machine learning (ML), and generative AI concepts, including their use cases and applications on AWS. This certification is ideal for professionals seeking to sharpen their competitive edge, position themselves for career growth, and potentially achieve higher earnings.

The exam, currently in its beta phase, consists of 85 questions to be completed within 120 minutes. It assesses a candidate’s understanding of key AI/ML concepts, including generative AI, and their practical application on AWS. The questions are a mix of multiple-choice and multiple-response formats, evaluating both theoretical knowledge and practical application skills. A passing grade for the exam is set at 70%, or a score of 700 out of 1000.

This certification is intended for individuals who are familiar with AI/ML technologies but do not necessarily build solutions using them on AWS. It caters to a broad range of roles, such as business analysts, IT support professionals, marketing professionals, product or project managers, line-of-business or IT managers, and sales professionals. By earning this certification, candidates demonstrate their ability to understand and leverage AI/ML technologies on AWS, enhancing their career prospects and expanding their professional capabilities in the rapidly growing field of artificial intelligence.

Preparing for the AWS Certified AI Practitioner exam required a strategic approach, given its comprehensive coverage of AI, ML, and generative AI concepts, especially as they apply to AWS services. My preparation journey began with selecting the right resources and creating a structured study plan to ensure I covered all the necessary material thoroughly.

I chose Stephane Maarek’s course on Udemy as my primary resource. This 6.5-hour video course offered an in-depth overview of the core topics needed for the exam, focusing on AI/ML fundamentals, AWS services, and real-world applications of these technologies. Over seven days, I dedicated time each day to watch the course videos and, importantly, took meticulous notes by hand on every key detail Stephane mentioned. This methodical note-taking process helped me retain information and provided a handy reference for reviewing critical concepts later.

In addition to the course, I supplemented my preparation with practice exams, also provided by Stephane Maarek. These practice exams were particularly valuable because they closely replicated the format and difficulty of the actual exam, each comprising 85 questions. I dedicated three days to completing three full-length practice exams, which was instrumental in building my confidence and refining my exam strategy. By consistently scoring between 90-95% on these practice exams, I felt reassured that I was well-prepared to meet the exam’s passing score of 70% (700 out of 1000).

On the day of the AWS Certified AI Practitioner beta exam, I felt a bit stressed, as this was my first experience with a beta exam format, and I wasn’t entirely sure what to expect. As I progressed through the exam, I noticed that many questions were not as straightforward as I had hoped; some were unclear, and others seemed to have two plausible answers. This ambiguity caused some confusion and took up more time than anticipated.

The exam had a strong focus on topics like Amazon Bedrock, Amazon SageMaker, and prompt engineering. However, thanks to the strategy I followed during my preparation, I was able to identify patterns in the questions and answers. I noticed that certain keywords in the questions often hinted at the correct answer, and in many cases, two of the answer choices were clearly irrelevant to the question at hand. This pattern recognition became a valuable tool for me. Whenever I encountered a question where I wasn’t sure of the answer, I could reliably eliminate two options that didn’t fit, significantly improving my chances of selecting the correct answer.

Despite the initial stress and some unclear questions, my preparation strategy and ability to recognize these patterns helped me manage my time effectively and maintain confidence throughout the exam.

Reflecting on my experience with the AWS Certified AI Practitioner beta exam, a few key lessons stand out. The exam’s beta nature meant some questions were unclear or ambiguous, and the question pool was larger at 85 questions. Despite these challenges, careful preparation and strategic study techniques helped me navigate the exam successfully.

For those considering taking this exam, my advice is twofold: if you’re a beginner and this is your first certification attempt, it might be wise to wait until the beta phase ends and take the final version of the exam. The final form is expected to have fewer questions (around 65) and improved question quality, making it a more straightforward experience. However, this choice means you will miss out on the opportunity to earn the AWS Certified AI Practitioner early adopter badge, a unique recognition for those who pass the beta exam. Weighing these options will help you decide the best path forward for your certification journey.

Taking the AWS Certified AI Practitioner exam in its beta phase was a challenging yet rewarding experience. It pushed me to thoroughly understand AI, ML, and their applications on AWS and allowed me to contribute to the shaping of the final exam format. While the beta exam came with its own set of challenges, such as ambiguous questions and a larger question pool, the strategic preparation and resource utilization paid off.

For those looking to earn this certification, especially beginners, consider waiting for the final version of the exam for a more streamlined experience. However, for those eager to get ahead and earn the early adopter badge, the beta exam offers a unique opportunity. Regardless of when you choose to take it, a solid preparation strategy will be key to your success.

Good luck to all future exam takers!



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