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Machine Learning · AI roadmap

You develop, deploy and operate machine learning models on AWS. This path starts with AI fundamentals (AIF) for the concepts, then goes deeper with ML engineering (MLA) and the higher-level specialty certification (MLS).

The machine learning path connects concepts and engineering in a single line. AIF is the introductory stage that sorts out concepts and terminology, including generative AI; MLA takes the engineering view of actually training, deploying and operating models; MLS requires broader specialist knowledge across ML. If you skip the concept stage, you will spend your time just interpreting terms in MLA pipeline questions. It is the only path with four steps, so it also takes the longest to prepare.

Certifications: 4
Curriculum length: 34 weeks · 170 days
Total exam fees: $650

Machine Learning · AI certification exams at a glance

Exam	Questions · Time	Passing score	Exam fee	Recommended level
CLF-C02	65 questions · 90 min	700 / 1000	$100	Foundational · No prior knowledge required
AIF-C01	65 questions · 90 min	700 / 1000	$100	Foundational · No prior knowledge required
MLA-C01	65 questions · 130 min	720 / 1000	$150	Intermediate · 1-2 years of relevant hands-on experience recommended
MLS-C01	65 questions · 180 min	750 / 1000	$300	Specialty · Hands-on experience in the domain recommended

How to study for the Machine Learning · AI certifications

AIF is an introductory exam that asks broadly about generative AI and machine learning concepts and responsible AI. Even if your role does not involve building models, start with AIF if you plan or adopt AI services.
MLA and MLS ask about the stages of data preparation, training, deployment and monitoring, centered on SageMaker. If you sketch out the features used at each stage like a map, you can see right away where a question sits.
Machine learning fundamentals such as evaluation metrics (precision, recall and so on) and how to deal with overfitting cannot be solved with service knowledge alone. Do not skip the concept explanations in those weeks.

Frequently asked questions

Which AI certification should I earn first, AIF or MLA?: AIF if you are in a planning or development role that uses AI; MLA if you are an engineer who trains and deploys models directly. If machine learning is new to you, the safe order is to learn the concepts with AIF and then move on to MLA.
Do I have to earn MLS (Machine Learning – Specialty)?: It is not required. It is a specialist stage that goes deep into machine learning theory and SageMaker operations, so we recommend taking it after MLA when you make machine learning your main focus.
Do I need to be good at math?: There are almost no questions where you calculate a formula. Instead, you need to understand concepts such as what an evaluation metric means and how to handle data imbalance or overfitting when they occur.
How long does it take to finish the Machine Learning · AI roadmap?: In the order CLF-C02 → AIF-C01 → MLA-C01 → MLS-C01, that comes to 34 weeks (170 days in total) of the CertNote curriculum. We based this on reading one day's lesson per day; if you have hands-on experience, you can move quickly through the weeks you already know. The exam fees add up to $650 in total.

The notes for every certification are free in every week. Prepare in order to fit your target role. Exam fees are based on the official AWS exam guides; exchange rates and taxes at the time of payment are extra.

Machine Learning · AI certification exams at a glance

Exam	Questions · Time	Passing score	Exam fee	Recommended level
CLF-C02	65 questions · 90 min	700 / 1000	$100	Foundational · No prior knowledge required
AIF-C01	65 questions · 90 min	700 / 1000	$100	Foundational · No prior knowledge required
MLA-C01	65 questions · 130 min	720 / 1000	$150	Intermediate · 1-2 years of relevant hands-on experience recommended
MLS-C01	65 questions · 180 min	750 / 1000	$300	Specialty · Hands-on experience in the domain recommended

How to study for the Machine Learning · AI certifications

AIF is an introductory exam that asks broadly about generative AI and machine learning concepts and responsible AI. Even if your role does not involve building models, start with AIF if you plan or adopt AI services.

MLA and MLS ask about the stages of data preparation, training, deployment and monitoring, centered on SageMaker. If you sketch out the features used at each stage like a map, you can see right away where a question sits.

Machine learning fundamentals such as evaluation metrics (precision, recall and so on) and how to deal with overfitting cannot be solved with service knowledge alone. Do not skip the concept explanations in those weeks.

Frequently asked questions

Which AI certification should I earn first, AIF or MLA?

AIF if you are in a planning or development role that uses AI; MLA if you are an engineer who trains and deploys models directly. If machine learning is new to you, the safe order is to learn the concepts with AIF and then move on to MLA.

Do I have to earn MLS (Machine Learning – Specialty)?

It is not required. It is a specialist stage that goes deep into machine learning theory and SageMaker operations, so we recommend taking it after MLA when you make machine learning your main focus.

Do I need to be good at math?

There are almost no questions where you calculate a formula. Instead, you need to understand concepts such as what an evaluation metric means and how to handle data imbalance or overfitting when they occur.

How long does it take to finish the Machine Learning · AI roadmap?

In the order CLF-C02 → AIF-C01 → MLA-C01 → MLS-C01, that comes to 34 weeks (170 days in total) of the CertNote curriculum. We based this on reading one day's lesson per day; if you have hands-on experience, you can move quickly through the weeks you already know. The exam fees add up to $650 in total.