How to Ace the AWS Cloud Practitioner Certification with Minimal Effort
By: Nicole Janeway Bills
Tags: Certification, Cloud Computing, Data Science, AWS, Amazon Web Services

This is a guide for anyone who is excited to spend less time studying and more time doing high impact work enabled by AWS products. Whether or not you’ve worked with AWS before, hopefully you’ll find this approach helpful on your journey to Cloud Practitioner Certification. Although Amazon recommends six months of familiarity with cloud architecture before sitting for the exam, with the right mindset for preparation, anyone can ace the exam in much less time.

The Cloud Practitioner Certification is the foundational level of Amazon’s 12 certification options, which include advanced tracks in Architecture and DevOps as well as specialty paths for Machine Learning, Data Analytics, Networking, and more. Getting AWS Certified can be a confirmation of job skills or the launching of a new career. Here’s a guide to passing the exam in three easy steps.

Ready to join me on cloud nine? Let’s get started!

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In this guide:

2. My experience getting Cloud Certified

3. Three steps to certification

4. Final thoughts on exam readiness

5. Next steps

1. Introduction to the AWS Cloud Practitioner Certification

The Cloud Practitioner exam consists of 65 multiple choice questions. Sometimes two or more options are correct — in this case you’ll be asked to identify all of the correct answers, and no partial credit is given.

You can take the exam at a test center or at your home or office with a video monitor. Sitting for the exam in a familiar setting is a great strategy — not only will you be more comfortable, you can potentially draw on the advantage of context-dependent memory. (Research, like this 2006 study, tells us if you studied for the exam mostly at your kitchen table, then taking the exam from your kitchen table might allow you get at some otherwise difficult to access memories).

When you pass the exam, the test provider will email within a couple hours with a score certificate. Sadly, they don’t provide any information about which questions were right or wrong. They do provide a breakdown by content area, which helps give a sense of areas of strength and weakness.

You can use your credential to attract more attention from recruiters, showcase your knowledge to potential employers, join a private AWS Certified Global Community LinkedIn group, and shamelessly make cloud puns.

As of this writing, the cost for the exam is $100. Check with your employer to see what they might do in terms of reimbursement.

2. My experience getting Cloud Certified

In this section, I’ll detail my experience with AWS. Feel free to skip. Otherwise, hopefully this is helpful if you’re looking to understand some AWS use cases, hear a potential studying approach, or enjoy some schadenfreude.

My journey with AWS has lasted about a year so far. It’s pretty much run in parallel with my path to becoming a Data Scientist. I started interacting with the O.G. cloud provider in Summer 2019. Despite knowing nothing about networking, I was facing a third round interview for Cloud Solutions Architect role at AWS in their networking specialty group. Spoiler, the interview went a little something like this:

Realistic depiction of my third round AWS Cloud Solutions Architect interview.

Anyway, in preparation, I crammed for two weeks to memorize the company’s Well-Architected Framework (this is important for the AWS exam), and also come up with personal example for each of Amazon’s 14 Leadership Principles (not tested by AWS but critical if you’re trying to land a job there) and learn the difference between TCP and UDP, security groups and NACLs, IPv4 and IPv6, stratocumulus and nimbostratus.

I also watched several YouTube videos showcasing the breadth of AWS product offerings. Nerdily, I think it’s pretty exciting to see all the different services offered under the AWS umbrella. I’d estimate that about 15 hours of studying at this stage became relevant later on.

After the epic shot block that was the third round technical interview, I took a little break from the cloud. It became directly relevant again in Winter 2019 when I was a Data Science student at Flatiron working on a volunteer webscraping project.

The objective was to populate a calendar of nature-focused outdoor events in the Washington, DC area. One of our teammates suggested automating the workflow using AWS Lambda and CloudWatch. It was cool to peek over his shoulder while implementing these tools and ultimately turning over responsibility to the client to run the workflow.

Throughout the Spring of 2020, I’ve consistently used AWS as a Machine Learning Engineer at Atlas Research to execute state-of-the-art deep learning for natural language processing (NLP). AWS provided the compute resources necessary to quickly and easily conduct sequence tagging with a BERT-based model.

For less than $75 a month, I’m able to spin up an EC2 instance that offers GPU computing power. The GPU part is critical — though they were designed originally to help video gamers achieve higher quality graphics, it turns out GPUs are also great at intaking unruly text data and returning orderly insights. The transformer architecture that underlies the latest advancements in NLP is designed to run efficiently on this kind of processor given their capacity to parallelize encoder stacks.

For these NLP projects, I store the text input (annotated sentences from medical journal articles) in an S3 bucket, and use a one-line HTTP call to import that data into Jupyter Notebook running on the EC2 instance.

Sample AWS machine learning workflow

When I sat down in early May to begin studying for the cert, I found it much easier than expected given recent hands-on experience and generally expanded knowledge-base.

I sat for the exam a month later after about 60 hours of studying during May and June. (All told, that’s around 75 hours of total study time.) I took the exam at home through Pearson Vue and passed with 869 out of a required 700 points.

The process of drilling was helpful at work as well. As a Data Scientist, it’s good to have a solid understanding of AWS’s capabilities and a framework for deploying best practice architecture. The most enjoyable aspect of studying was seeing everything that AWS has to offer across many different use cases and job functions. The Cloud Practitioner Cert makes it pretty easy to start thinking about how different workflows can come together to execute a task.

Three steps to certification

If you’re ready to start taking this exam cirrus-ly, use this three step process to ensure your studying is quick and easy.

Step 1 — Use the Feynman Technique

Richard Feynman was a Nobel Prize winning American theoretical physicist who played an integral role in the formulation of quantum mechanics. Throughout his life, Feynman was all about taking extremely complex ideas (concepts way more complicated than anything you’re going to hit on in your studies of AWS) and distilling them into simple means of communications like diagrams and pop-science books.

Feynman was distinguished by his approach to learning. You can utilize his observations about studying to help gain mastery of any subject. Let’s apply his ideas to the AWS exam.

On the title page he wrote: Notebook Of Things I Don’t Know About.

Before you even get started, try to figure out what you don’t know about the topic at hand. Throughout your studies, add to this notebook, indicating areas for further study.

I chose to organize my thoughts in a series of mind maps, linking concepts based on their similarities, but you can use whatever approach makes sense to you.

By organizing your knowledge in this way, you’re ensuring that you focus on the gaps in your knowledge. Don’t waste time studying things you already know because it’s comforting.

As you study, other elements of the Feynman Technique may be helpful to you:

Teach the ideas to someone else

Return periodically to the source material to fill in gaps

Constantly seek to simplify your explanations at the core of each product or idea

Create analogies that help these concepts feel intuitive

Although the AWS exam is a test of memorization, you will benefit from sowing fertile ground from which these details can grow.

Step 2— Take a practice test

Buy a set of practice exams (here is the set I purchased for $12.99 in May 2020). Pick one exam and work through it as though you’re taking the real test.

Taking a practice test promotes familiarity with the exam style. This approach enables you to train to the test throughout your study time.

Then depending on your score and study style, pick a path to structure your review:

Fast Track — over 50% correct, requiring 20–50 hours of study time

— over 50% correct, requiring 20–50 hours of study time Slow Track — under 50% correct, requiring 50 to 75 hours of study time

Based on your practice test score in each specific section, you’ll have a good sense of what to focus on.

Step 3— Watch the official Training and Certification video series

AWS offers 6 hours of videos to prepare you for the Cloud Practitioner Cert. The content is bucketed into the five areas of Core Services, Integrated Services, Architecture, Security, Pricing and Support.

Watch at least some of these training videos, which range from a couple minutes to 20 minutes long. This content will help you better understand AWS focus areas and get you familiar with the vocabulary the team uses to talk about their products. In my opinion, this familiarity is valuable for eliminating incorrect answers when test taking (i.e., if an answer doesn’t sound like it was written in the AWS “voice,” then it’s probably not right).

The videos do not cover all the information you’ll need to know for the exam — you should also plan to skim AWS white papers — but they’re a good starting place. Each video starts with a different presenter talking about a product, service, or concept and how it’s used. Then there’s often a demo. This is potentially helpful for solidifying concepts, but for maximizing your study time, skip these sections since no new info is introduced.

There are knowledge checks (very easy questions) interspersed throughout the videos, and the series concludes with a Final Course Knowledge Check composed of 30 questions that accurately represent difficulty levels seen in the real exam.

Fast Track

Of the five areas listed above, start with the content you scored lowest on during your practice exam. Thoroughly review and look over the relevant white papers. Then take another practice exam and see what information you need to go back and research in greater detail. Continue working through content areas from weakest to strongest.

Slow Track

If you’re relatively new to AWS, I recommend watching all the videos in order. Don’t forget to check out the corresponding white papers. As you gain confidence, try another practice exam. I think you’ll be pleasantly surprised by how quickly the material comes together for you!

Final thoughts on exam readiness

Once your practice exams are consistently in the 80% and above range, you should be good to take the AWS exam. Work your way methodically through the questions, knowing that you can return to any on which you get stumped.

Given that the test is multiple choice, it evaluates your ability to eliminate incorrect answers / recognize correct ones. Sometimes the questions are tricky, as when focused on a less common product or on the intricacies of a particular service. Also, some questions ask you to select multiple correct answers (i.e., “chose two”). There is no partial credit, so this question type increases the overall difficulty of the exam.

Passing requires getting above 700 out of 1000 total points. This is totally doable. After 75 hours of studying, I took the exam at my kitchen table and scored a 865. I’m feeling weightless now the burden studying has been lifted — cloud pun very much intended.

Photo by Rakicevic Nenad on Pexels

Research shows that testing is helpful for knowledge formation. If you suffer from test anxiety, this can be a useful thing to keep in mind. Try to tell that inner voice of worry that you’re not taking a test, you’re solidifying knowledge that will make you an effective cloud practitioner.

Next Steps

A frustrating thing about the certification process it’s just a test of memorization. It doesn’t actually help you deploy or troubleshoot AWS resources.

Just like any aspect of computer science, working with the AWS environment is not always a smooth experience. Fortunately, there’s a lot of good community content made by people more patient than I for when you hit a stormy patch.

Are you planning to use these strategies to study for the exam? If you’re already certified, how did your study plan compare? If you found this article helpful, follow me on Medium, LinkedIn, and Twitter for more ideas to advance your data science skills.