Want to start your journey in AI and cloud with AWS? The AWS Certified AI Practitioner (AIF-C01) certification is designed for beginners to learn the basics of artificial intelligence, machine learning, and generative AI, using tools like Amazon Bedrock and Amazon SageMaker.
In this step-by-step guide, you’ll find a practical roadmap to prepare for the AIF-C01 exam in 2025, complete study plans, resources, and expert tips to pass confidently on your first attempt.
What You’ll Learn in This AWS AIF-C01 Certification Guide
- Efficient ways to prepare for AWS AIF C01
- Study resources to hands-on practice
- Weekly study plan and actionables for AIF C01
- How AWS turns generative AI into real solutions.
AWS AIF-C01 Certification Roadmap for AI Fluency in 2025
The line between cloud and AI is disappearing very quickly. Apart from knowing how to build, deploy and prompt AI models, there is a lot more to uncover. With the emergence of the new digital literacy.
Why Do AI and Cloud Skills Now Go Hand-in-Hand
For the record, 2025 has seen more than 60% of AWS learners start their AI journey with AIF-C01. The conversation today has shifted from “What can AI do?” to “How can I use AI responsibly and effectively in the cloud?”. AWS AIF C01 is the answer to this question, as it concentrates on making any role, from data beginners to cloud engineers, build seamless AI workflows fluently.
How AWS Turns Generative AI into Real Solutions
Services like Amazon Bedrock power generative AI models directly within AWS ecosystems, and Sagemakers train, fine-tune and deploy custom models; the wall between AI and cloud is moved out. As AWS learners begin their AI journey with AIF-C01, for everything from data analytics to automation roles, this skill isn’t just a specialisation but is required to survive in tech.
What Is AWS AIF-C01 Certification?
Overview of AWS Certified AI Practitioner Exam
The AWS certified AI Practitioner AIF C01 certification is live from 2024, an entry-level AI certification that is designed to evaluate the foundational skills and understanding of Artificial Intelligence (AI), Machine Learning (ML) and Generative AI on AWS. There is not much testing of coding models or solving heavy math.
Key Benefits of Earning AWS AIF-C01
The exam is about validating how well you get to understand AI services like Amazon Bedrock and SageMaker in real-world business environments and apply them responsibly with AI principles for effective working. The certification bridges the gap between business professionals, data-curious developers, and cloud beginners to speak AI language confidently. More like a literacy test to survive and upskill in the cloud-first era.
AWS AIF-C01 Exam Pattern and Details
This certification is perfect for anyone curious about how AI elevates cloud computing, product innovation, and business decisions effectively.
Exam Format and Difficulty
| Details | Description |
| Type | Multiple Choice / Multiple Response |
| Questions | 65 questions to answer |
| Duration | 90 minutes |
| Fees | $ 100 |
| Validity | 3 years |
| Difficulty Level | Foundational Level – no coding or math required |
| Recommended Knowledge | Basic understanding of IT, AWS cloud, etc. |
| Focus Areas | AI/ML concepts, AWS AI services (Bedrock, SageMaker), Responsible AI |
Step-by-Step Preparation Guide for AWS AIF-C01 Exam in 2025
Here is a complete breakdown of where to start your AWS Certified AI Practitioner exam, from understanding domains to setting up your desk for the actual exam. Scroll down to get detailed preparation metrics.
Step 1: Understand the Exam Domains and Weightage
Before you start with the preparation, it’s important that you understand what you are being tested for. The AWS AIF C01 tests the following five major domains, measuring your ability to connect AI theory with AWS services in real-world contexts.
| Domain | Weightage | Key Topics |
| AI Concepts | 25% | AI/ML/Generative AI basics |
| AWS AI Services | 30% | Bedrock, SageMaker, Comprehend, Lex |
| Responsible AI | 20% | AI ethics, privacy, compliance |
| Foundation Models | 15% | Prompt design, fine-tuning |
| Security | 10% | Safe AI deployment |
The AWS AIF C01 exam draws a clear difference between Generative AI and Traditional AI. While Gen AI works on possibilities, Traditional AI focuses on prediction and automation.
Difference Between Traditional AI and Generative AI
| Aspect | Traditional AI | Generative AI |
| Goal | Predict or classify | Create or generate |
| Example Tasks | Spam detection, sales forecasting | Text, image, or code generation |
| Key AWS Services | SageMaker, Comprehend | Bedrock, Titan Models |
| Data Dependency | Structured historical data | Pre-trained on massive unstructured datasets |
| User Interaction | Input–output logic | Conversational and creative |
Traditional AI tells you what will happen, while Generative AI shows you what’s possible.
Step 2: Build Your AWS AIF-C01 Study Plan
Be it me, you, or anybody, we all have and are searching for “How to create an AIF C01 study plan?”, “Give me sample Study plans for AWS AIF”, and a lot of other keywords. But here, you will find a Cumulative Study plan that fits all your situations. This is going to be a smart mix of concepts with consistent practice and real AWS playtime.
14-Day Study Plan for 2025
| Day | Focus Area | Key Resources |
| 1–3 | AI basics & terminology that are supervised vs unsupervised, training vs inference. | Whizlabs videos, AWS Docs, such as Intro to AI/ML, GenAI concepts |
| 4–6 | Generative AI concepts, from prompts, foundation models, to use cases. | Whizlabs Bedrock Labs, Amazon Q&A Tutorials, and Skill Builder give you a complete overview of Generative AI. |
| 7–9 | AWS AI Services like SageMaker, Comprehend, Lex, Polly, and Transcribe. | AWS Free Tier Sandbox, Whizlabs Hands-on Labs, AWS Sandbox |
| 10–12 | About responsible AI & Prompt Engineering, including ethics, privacy, and fairness. | Whizlabs Ethics Module, AWS Responsible AI Course |
| 13–14 | Full Practice exams + Review and reworking weak areas. | AWS AIF free practice Test, and a few paid ones from Whizlabs and others (if you want), the Dashboard gives a clear understanding of your strengths and weaknesses to analyse with different practice test modes. |
Customize Your Study Plan Using AI Tools
You can also use Gen AI tools to customise this plan for your availability and get it planned with your available resources, time to spend, how to value outcomes and move forward. With specification, you can actually attain a better custom plan, but it’s all in the action you take to follow and pass your AWS AIF C01 in 2025 or later (when you decide to take the test).
Step 3: Step-by-step Preparation Strategy of AWS AIF C01 Exam
This is a breakdown of what the major must-knows are and how you can analyse your progress in every step.
1. Understand the AI language.
While preparing for the AWS AIF C01 exam, start with understanding how AI actually thinks, works and executes. Instead of deep diving into equations, grasp the rhythm of how machines learn from data, which are supervised and unsupervised. What is happening in the training phase and during the inference phase, and how LLMs like ChatGPT, Amazon Q are different from the older systems.
To evaluate your progress in this particular concept, you can seamlessly talk about it in a flow without any notes. When you can discuss openly in your own style and words with real-world analogies, like comparing AI training to schooling a kid, then you are on track. Go ahead!
2. Learn AWS AI services.
The next step is to move from concepts to AWS tools. Instead of just reading AWS Bedrock, SageMaker, Rekognition, Polly, Lex, Transcribe, and Comprehend, spend time working on them, exploring their properties and seeing what their actual actions are like. The concepts majorly deep dive into these AWS Tools for performance efficiency. SageMaker to build AI models, Bedrock for generative AI, Rekognitions does the image analysis part, and Lex converts bots.
Test yourself answering questions like which AWS service is best for a given AI task, why you’d use Bedrock over SageMaker for generative projects, and more. Formulate such a question to bridge between problem statements and the right services.
3. Exploring Real Use Cases
Now is the time to explore hands-on with real-time use cases. Theory meets real-world expertise. Understand how AI is used on AWS by brands to automate certain aspects of their process. Like automating customer support with Lex or analysing social media tone with Comprehend. Explore services with their use cases and try to answer real-time questions.
Answer a few more technical questions, like “What business goal did AI solve in this particular situation”? Which AWS service made it possible? Could I sketch a similar workflow for another industry? To test your level of understanding. This preparation is more than exam readiness, but real-time implementation where you think and get ready to act as an AI practitioner.
4. Practice and assess your progress
Take up real-time practice tests from Whizlabs. We have practice tests with different modes, like practice and Exam mode. Where you can take section-wise practice tests and a real exam mode experience, giving a real feel that stays as a practice for you. And during the exam day, there is no need to fear. The review option in the Practice tests allows you to revisit and analyse after you finish every other question.
With this, you can analyse based on the mark you get in the practice exams, get clarity on how many questions were answered and the answers that were right. Revisit the concept behind each wrong answer. Find the gap and take your next move to bridge it.
5. Revise the Smart way.
Once you are confident with your preparation and focus on giving clarity to your preparation and don’t cram. Summarise every domain like one-pagers and short voice memos. “Learn it, Apply it and teach it” This rule of three will help you understand any concepts practically. At the end of this phase, you get to understand how to solve a problem rather than just knowing Sagemaker or Bedrock. A true reward for your AWS AIF C01 rewards.
Step 4: Practical Learning with Hands-on Labs
Let me break the truth: if you have to build anything AI, reading helps, but doing and running actual prompts or deploying models is different. For this, try labs. There are dedicated labs and sandboxes for Generative AI in Whizlabs, which help you dive into real AWS scenarios, from building text-generation prompts in Bedrock to using Amazon Q for analysing datasets automatically and deploying, testing and optimising ML models in SageMaker.
The labs walk you through AWS Consoles where you touch, use and understand the tools in real time. This practice strengthens your use-case understanding, which is a must to study domains in AIF-C01.
Step 5: Go a step beyond, Learn Prompt Engineering
Prompt engineering is a core skill to interact with AI, and for AIF C0,1, this is an added advantage. With prompt engineering, it’s like talking to an AI system to give exactly what you want. Here you learn to guide them instead of guessing how to model with clarity, context and creativity.
Step 6: Review Responsible AI & Ethics
With all the practice tests and lab interactions, understanding the responsibilities of AI and Ethics. Responsible AI isn’t about memorising ethics but making judgments in tricky, real-world Scenarios.
Resource Library for AWS AIF C01
| Type | Resource | Platform |
| Free Learning | AWS Skill Builder – AI Learning Plan | AWS |
| Practice Tests | AIF-C01 Practice Exams | Whizlabs |
| Official Docs | AWS AI Services Overview | AWS |
| Hands-on | AWS Free Tier + Labs | AWS |
| Videos | AWS Training YouTube Channel | YouTube |
AWS AIF C01 Exam Day Mindset and Common Mistakes to Avoid
First things first, keep your pace steady and don’t get stuck rereading tricky questions. Leave them, and proceed with what you are confident about first, and then revisit the rest. As the scenario questions have two “good” answers, pick the one that aligns with AWS’s core principles, such as scalability, security, and management.
In case of common pitfalls, don’t ignore the Responsible AI domain, case study examples. Don’t spend too much time trying to learn the code. This AWS AIF C01 exam is to test your AI fluency and not data science math. Stay calm, confident, and curious.
What’s next after AWS AIF C01?
After you pass the AWS AIF C01 exam, build your momentum and move to the next logical steps, such as AWS Certified Machine Learning Speciality. Dive into a hands-on GenAI project using Bedrock and SageMaker. These certifications add value to your position in product, marketing, data, or cloud strategy and bridge the gap between business understanding and technical AI adoption.
This certification doesn’t just prove you “know” AI, but where it’s headed. So, as you start applying in your daily task that contributes to AI-driven solutions in your workplace. Add experience and open the door to better placements and progress.
Frequently Asked Questions
1. How many weeks should I study for AIF-C01?
Most learners prepare in 2–3 weeks with daily study (1–2 hours/day). If you’re new to AI, extend to 4–5 weeks to include hands-on labs.
2. Is coding required for AIF-C01?
Nope. You don’t need any programming experience. The exam mainly focuses on AI literacy, not building models.
3. Do I need AWS experience for hands-on labs?
No. All Whizlabs and AWS Skill Builder labs are beginner-friendly. They guide you through the real AWS console.
4. What is prompt engineering in AIF-C01?
It’s the skill for writing effective prompts that guide AI systems like Amazon Bedrock or AmazonQ to produce accurate and ethical outputs.
5. What is Responsible AI in AIF-C01?
Ensuring fair, ethical, and secure use of AI. You’ll be tested on bias, transparency, data security, and governance principles.
6. How often does AWS update the AIF-C01 exam?
The AWS AIF C01 certification validity is 2–3 years to align with new AI/ML services.
7. How can I access free AIF-C01 practice tests?
You can start with Whizlabs’ free Practice test, the AWS Skill Builder practice exam, or community quizzes shared on platforms like Reddit and LinkedIn Learning groups.
Conclusion
The AWS Certified AI practitioner (AIF C01) exam isn’t about earning a badge. It completely understands how AI thinks and works in its language. Every hour you spend in preparation with concepts, practice tests, hands-on labs and Sandboxes, you get closer to solving real-world problems with AI automation, with an efficient understanding of AI Models.
The AIF C01 isn’t about just passing, but understanding how AI reshape cloud roles, workflow and opportunities. This is a skill that’s evolving to be non-negotiable in today’s AI world. Gen AI tools like Bedrock and SageMaker JumpStart will evolve, but the foundation you build with AIF C01 makes your skill adoptable.
Get started with your prep for AWS AIF-C01 today with Whizlabs, practice tests, hands-on labs and Sandboxes, and dive into your AI journey confidently.
- Step-by-step guide to prepare AWS AIF-C01 in 2025 - November 3, 2025
- 7 Reasons to Get Scrum Master Certification in 2025 - September 30, 2025
- Top Microsoft Azure Courses to Learn in 2025 - September 17, 2025
- Top Cloud Computing Courses to Learn in 2025 - September 10, 2025
- How to Pass the GH 900 GitHub Foundation in 2025? - August 6, 2025
- Salesforce Agentforce Passing Guide and Career Roadmap - July 10, 2025
- Top 7 Mistakes To Avoid While Preparing For AZ 104 Exam - June 28, 2025
- Is Model Monitoring & Debugging Critical for AWS MLS C01? - June 20, 2025