After recently posting about our experiences with the new AWS AI Practitioner (AIF-C01) and AWS Machine Learning Engineer Associate (MLA-C01) certifications, we were overwhelmed by the number of enthusiastic people who reached out with questions. In response to this incredible interest, we decided to write this article to share our insights with a broader audience of cloud and AI enthusiasts.
Who are we?
We’re Bangaly Kaba, PhD, and Miklós Csécsi, two cloud enthusiasts at different stages of our AWS and cloud journey. We recently sat down to chat about our experiences with the new AWS AI Practitioner (AIF-C01) and AWS Machine Learning Engineer Associate (MLA-C01) exams.
Bangaly is a Senior Tech Lead & Cloud Architect with over 20 years of experience, including a role as a CISO. He holds a PhD in Computer Science, specializing in data mining and natural language processing, as well as a TOGAF certification in enterprise architecture. Bangaly's expertise spans cloud architecture, blockchain, data analysis, and machine learning. He's fully certified in multiple cloud platforms and Kubernetes and has a deep background in AI and machine learning. In his current role at Société Générale, he designs and implements innovative solutions for the banking sector. Bangaly’s impressive career includes work on semantic data processing, encryption and decryption modules, secure exchange connectors, single sign-on authentication, and anti-ransomware defense strategies. He’s also experienced in designing payment and messaging applications for numerous operators across multiple countries.
Miklós comes from a High-Voltage Electrical Engineering background and has a diverse career in technology. He worked as a Senior Software Developer at Siemens, working on safety- and security-relevant software.Later, he transitioned to a Senior Security Solutions Engineer role, specializing in Application and Cloud Security, working for companies like Snyk and Rapid7.
Throughout his career, Miklós has had the opportunity to collaborate with over 250 companies across more than 15 countries, focusing on Cloud- and Application Security and Vulnerability Management. With around five years of hands-on cloud experience and multiple AWS certifications, Miklós is now preparing to start a new chapter as a Solutions Architect at AWS. He has also had the privilege of speaking at several events, from Hamburg through Bern to Cape Town, where he shared insights on cloud and network security. Additionally, he regularly holds workshops and enablement sessions on cloud and IT Security.
Miklós: Bangaly, it's great to catch up! I know you've recently passed both the AI Practitioner and ML Engineer Associate exams. What was your motivation for taking these?
Bangaly: Well, Miklós, I took these exams to expand my knowledge and skills in AI and ML, as they’re rapidly advancing technologies with numerous applications across industries. Additionally, having these certifications can enhance my career prospects and open up new opportunities.
Miklós: I completely agree. I'm convinced that AI will be as transformative as the internet was in its early days. What kind of experience did you have with AI before pursuing these exams?
Bangaly: I share your enthusiasm for the transformative potential of AI! Before taking these exams, I had some exposure to AI through online courses and tutorials but wanted a more comprehensive understanding of the field. The exams provided me with a structured learning path and the opportunity to apply my knowledge in real-world scenarios.
Miklós: My background is a bit different. I studied High-Voltage Electrical Engineering, which included coursework in Advanced Mathematics, Stochastics, and Programming. But I haven’t applied AI concepts directly in my professional work yet. When did you first encounter generative AI?
Bangaly: Your background in Electrical Engineering and your knowledge of Advanced Mathematics and Programming will definitely come in handy for your AI journey.
I first encountered generative AI at AWS re:Invent 2023 and later at Google Cloud Next '24, where I was introduced to generative adversarial networks (GANs) for image generation. It was amazing to see how these networks could create realistic images from random noise. Since then, generative AI has evolved a lot and is now widely used in things like image, speech, and text generation.
Miklós: For me, it was about four months ago at the AWS Summit in Berlin. Viktoria Semaan’s session opened my eyes to the possibilities of generative AI. Have you been using AI at work?
Bangaly: That's great to hear! Viktoria Semaan's session must have been quite inspiring!
I've been using Copilot in my work for about a year now. It’s a powerful AI tool that assists with coding, provides suggestions, and helps streamline workflows. I’m aiming to work on a project involving natural language processing (NLP) and computer vision (CV) to analyze large amounts of text and images. AI can be instrumental in helping us extract valuable insights from that data.
Miklós: That’s really interesting. To be honest, I haven’t used much of my university knowledge since graduating 6-8 years ago, but lately, I’ve started using AI tools like ChatGPT to make my daily work easier. It’s really like having an assistant for tasks like drafting emails, brainstorming ideas, or getting quick answers, which frees me up to focus on more strategic work.
How did you find the new AWS exams?
Bangaly: It's wonderful that you're incorporating AI tools into your work - they can certainly enhance productivity and efficiency!
Regarding the exams, I found them to be challenging but rewarding. The exams covered a wide range of topics, and I had to study and practice extensively to ensure that I was well-prepared. The exams also required me to apply my knowledge in real-world scenarios, which was a great way to solidify my understanding of the concepts.
Miklós: I completely agree, and congratulations on passing! I'm curious about your experience with the ML Engineer Associate exam. I have it scheduled in three weeks and am preparing with the official AWS courses and some Udemy ones. How did you find the difficulty level, and which study materials aligned best with the actual exam?
Bangaly: Thank you, Miklós! The exam was challenging but manageable with proper preparation. A solid understanding of fundamental concepts and AWS services is crucial. I found the official AWS courses helpful since they provided a structured learning path. Everyone’s study habits differ, but I recommend finding what works best for you.
Miklós: That’s really helpful, thank you. Do you have any last-minute tips for someone about to take the exam?
Bangaly: Well, as you approach the exam, it's important to remember to take your time and carefully read the questions. Some questions may require good analysis or apply your knowledge in a specific context, so it's important to understand the question and the scenario before answering.
Review the Exam Prep Plan course on AWS Machine Learning - Associate (MLA-C01).
Read the official exam guide carefully. Understand the domains, tasks and In-scope Aws services and features. For services involved in ML lifecycle, have a look in corresponding aws faq docs.
Additionally, it's a good idea to take practice exams to get a feel for the exam format and the types of questions that are asked. This will help you identify areas where you need to focus your study efforts.
Finally, don't forget to take care of yourself during the exam. Make sure to get enough sleep the night before, eat a healthy meal, and stay hydrated. Taking care of yourself can help you perform at your best on the exam.
Miklós: I appreciate the insights, Bangaly. I'm curious, what topics did you find most prominent in the new AI Practitioner exam? I'd love to compare notes.
Bangaly: For the AI Practitioner exam, the topics I found most prominent were related to large language models, prompt tuning, fine-tuning, RAG (retrieval-augmented generation), responsible AI, as well as model-related aspects like cost, accuracy, security, and performance. Services like Bedrock, SageMaker, and AWS ML managed services also played a key role.
How did you find the AI Practitioner exam?
Miklós: That’s interesting. I found a large portion of the AI Practitioner exam focused on Bedrock and SageMaker, too.
I found AWS Skillbuilder to be a great resource, especially their Enhanced Exam Prep Plan, which includes about 15 hours of material (with a subscription) and a free set of 20 official practice questions that mirror the exam format. The plan finishes with a 60-70 question quiz that’s identical to the official exam in style and comes with detailed explanations, which I found really helpful.
I can also recommend Stéphane Maarek’s Udemy course that covered the exam topics well, and also the Cloud Quest Series on AWS Skillbuilder were a great resource.
I also have to add: the exam has 85 questions (longer than the usual 65), so everyone should prepare for an extended session!
Did you encounter questions on prompt engineering or measuring the performance of Foundation Models?
Bangaly: Yes, I did! Prompt engineering came up in both exams: the AI Practitioner exam had a few questions on prompt engineering, while the ML Engineer Associate exam had a few questions on measuring the performance of Foundation Models.
Miklós: That’s very insightful. Prompt engineering really shows how we can guide AI to produce more accurate outputs. With all the advancements, we’ll also need to watch out for risks like hallucinations or data leaks.
How do you see yourself applying this AI and ML knowledge in your current role?
Bangaly: That's a great point! The potential risks and new challenges associated with generative AI are indeed significant, and it's important for ML engineers and security pros to stay vigilant and address these issues as they arise.
Regarding how I see myself applying this AI and ML knowledge in my current role, I work on a team that develops and maintains a large-scale machine learning platform. This platform is used by many teams across our organization, and my job is to ensure that it is reliable, scalable, and efficient. I use AI and ML techniques to improve the performance of the platform, automate certain tasks, and provide insights to our users.
In terms of how I think this knowledge will shape my future career path, I see myself continuing to work on projects that involve AI and ML. I am particularly interested in natural language processing and computer vision, and I would like to explore these areas further. I also see myself taking on more leadership roles, where I can help guide the development of AI and ML technologies within our organization.
Miklós: That's fascinating. In my new role as an AWS Solutions Architect starting in October, I’m excited to help companies leverage AI and ML. I think there’s huge potential to optimize processes and create innovative products across industries.
Do you see any particular industries where AI and ML will have the biggest impact?
Bangaly: That's great to hear! As an AWS Solutions Architect, you will have the opportunity to help companies leverage AI and ML technologies in a variety of ways. Some of the industries that I see having the biggest impact in the near future include healthcare, finance, and retail.
In healthcare, AI and ML can be used to improve patient outcomes, reduce healthcare costs, and accelerate drug discovery. For example, AI can be used to analyze medical images, predict patient outcomes, and develop personalized treatment plans. In finance, AI and ML can be used to detect fraud, optimize investment portfolios, and improve risk management. For example, AI can be used to analyze financial data and identify patterns that may indicate fraudulent activity. In retail, AI and ML can be used to improve customer experience, optimize supply chain management, and develop personalized marketing campaigns. For example, AI can be used to analyze customer data and recommend products that are likely to be of interest to them.
Miklós: Those are some really interesting perspectives! I agree that the potential is enormous. It's both exciting and a bit daunting to think about how quickly the field is evolving.
Do you think we'll need to be constantly upskilling to keep up with the pace of AI advancements?
Bangaly: Yes, the pace of AI advancements is indeed rapid, and it's important for professionals to be constantly upskilling to stay relevant. This can involve taking courses, attending conferences, and reading research papers. One thing that I find particularly interesting is the intersection of AI and other fields, such as robotics, natural language processing, and computer vision. These fields are rapidly evolving, and it's important for professionals to be able to work across these boundaries.
How do you plan to keep up?
Miklós: I suppose that’s why certifications are so valuable - they keep our skills sharp. I plan to continue my learning path with the ML Engineer Associate exam, and after that, I’m considering the AWS ML Specialty exam to dive deeper into more advanced topics.
In addition to certifications, I’m planning to get more hands-on experience through personal projects and by applying ML in real-world scenarios. Working on practical use cases will help me stay on top of the latest trends and give me the chance to explore new technologies like computer vision and NLP.
I have to say, it’s been great discussing this with you, Bangaly, I feel even more motivated now to delve deeper into AI and ML. Thanks for sharing your experiences!
Bangaly: It's been my pleasure, Miklós. Best of luck with your ML Engineer Associate exam - I’m sure you’ll do great!
And to all the learners out there preparing for AWS AI certifications - whether it's the AI Practitioner, ML Engineer Associate, or any other exam - we wish you the very best of luck! Remember, the journey of learning is just as important as the destination. Stay curious, keep practicing, and don't be afraid to dive deep into these fascinating technologies.
Miklós: Thank you! And congratulations again on your certifications. Your insights have been invaluable!
As a closing note: I couldn't agree more, Bangaly! Good luck, everyone! The world of AI and Machine Learning is exciting and full of opportunities. These certifications are a great step towards being part of that future. Study hard, but also enjoy the learning process. You've got this!
Recommended study materials
Based on our experience, here are some study materials we found really helpful for preparing for the AWS AI certifications. Keep in mind, this is just our perspective - there are many other great resources out there!
AWS AI Practitioner (AIF-C01):
Stéphane Maarek: Ultimate AWS Certified AI Practitioner AIF-C01
AWS SkillBuilder official resources:
Enhanced Exam Prep Plan: AWS Certified AI Practitioner (AIF-C01)
(https://explore.skillbuilder.aws/learn/lp/2194/Enhanced%2520Exam%2520Prep%2520Plan%253A%2520AWS%2520Certified%2520AI%2520Practitioner%2520%28AIF-C01%29)
Exam Prep Official Practice Question Set: AWS Certified AI Practitioner (AIF-C01 - English)
(https://explore.skillbuilder.aws/learn/course/19790/Exam%2520Prep%2520Official%2520Practice%2520Question%2520Set%253A%2520AWS%2520Certified%2520AI%2520Practitioner%2520%28AIF-C01%2520-%2520English%29)
AWS Summit Berlin 2024 - Building an AWS solutions architect agent with Amazon Bedrock (BOA305) (https://www.youtube.com/watch?v=8ftKjZyaqNk)
Google Cloud CloudSkillBoost: Beginner: Introduction to Generative AI Learning Path (https://www.cloudskillsboost.google/paths/118)
Didn’t use personally all of these, but still very good content:
Frank Kane: Mastering AWS Certified AI Practitioner AIF-C01 - Hands On!
Tiny Technical Tutorials (https://www.youtube.com/@TinyTechnicalTutorials)
AWS Machine Learning Engineer (MLA-C01):
Stéphane Maarek & Frank Kane: AWS Certified Machine Learning Engineer Associate
AWS SkillBuilder: Enhanced Exam Prep Plan: AWS Machine Learning - Associate (MLA-C01)
https://explore.skillbuilder.aws/learn/public/learning_plan/view/2192/plan
AWS SkillBuilder: Exam Prep Enhanced Course: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)
https://explore.skillbuilder.aws/learn/course/external/view/elearning/19876/exam-prep-enhanced-course-aws-certified-machine-learning-engineer-associate-mla-c01-english
AWS SkillBuilder: Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)
https://explore.skillbuilder.aws/learn/course/external/view/elearning/19742/exam-prep-official-pretest-aws-certified-machine-learning-engineer-associate-mla-c01-english
AWS SkillBuilder: Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)
https://explore.skillbuilder.aws/learn/course/external/view/elearning/19688/exam-prep-official-practice-question-set-aws-certified-machine-learning-engineer-associate-mla-c01-english
You might also find useful - if you wish to dive deep into AI:
AWS SkillBuilder: Enhanced Exam Prep Plan: AWS Certified Machine Learning - Specialty (MLS-C01)
https://explore.skillbuilder.aws/learn/public/learning_plan/view/2190/plan
Frank Kane: Complete hands-on machine learning and GenAI tutorial with data science, Tensorflow, GPT, OpenAI, and neural networks (also advanced study materials)
https://www.udemy.com/course/data-science-and-machine-learning-with-python-hands-on
Basically all DeepLearning.AI (available on Coursera):
https://www.coursera.org/search?query=deeplearning.ai
Conclusion
As cloud enthusiasts at different points in our journeys, we both see a lot of value in continuous learning, especially with how fast AI is evolving. Whether you’re a seasoned pro like Bangaly or newer to cloud AI like Miklós, these AWS certifications are a great way to build your knowledge and stay ahead.
But it’s not just about passing the exam - it’s about really understanding how to use these technologies to solve real-world problems. As AI keeps changing the game across industries, having this knowledge will be a huge asset for anyone in tech.
Top comments (0)