Dataiku ML Practitioner
Dataiku ML Practitioner Certificate
More study resources
Cheat sheet
Keep the key ideas within reach.
ExploreKey terms
Get comfortable with the vocabulary.
ExploreStudy plan
Give each week a clear focus.
ExploreCommon mistakes
Understand the traps and how to avoid them.
ExploreCase studies
Put your knowledge to work in context.
ExploreExam-day guide
Prepare for the day ahead.
ExploreAbout this exam
The ML Practitioner Certificate is one of the certifications offered through Dataiku Academy, the learning arm of the Dataiku platform. According to the Academy catalog, the certificate validates knowledge of topics such as visual machine learning and interactive statistics - the two areas a practitioner uses when building models with Dataiku's visual tools rather than code. The catalog tags the credential toward roles including data scientist, data engineer, and citizen data scientist, so it suits analysts and model builders who work primarily through the point-and-click interface and want a structured way to prove that skill. The associated learning path is described as honing skills on the visual tools in Dataiku for building machine learning models, and the Academy lists individual recommended courses such as Machine Learning Basics, Scoring Basics, and Interactive Statistics that map onto the two domains. The exam itself is listed at 120 minutes. Candidates should note that the Academy states access to a certification exam requires first completing the upstream certifications shown in its prerequisite diagram, so check that ordering before scheduling. This page is an independent study resource and is not affiliated with or endorsed by Dataiku; always confirm current details on the official Academy site before you book.
What you'll study
About Dataiku ML Practitioner preparation
How long is the ML Practitioner exam, and how many questions does it contain?
The Dataiku Academy certification listing gives the ML Practitioner Certificate a duration of 120 minutes. The source does not publish a question count, so treat any specific number you see elsewhere with caution and plan your pacing around the clock rather than an item count.
What topics does the exam cover?
The Academy describes the certificate as validating knowledge of topics like visual machine learning and interactive statistics. In practice that means the visual model-building workflow in Dataiku - preparing and scoring data, training and comparing models - plus the visual statistics tools used for exploration and analysis.
Are there prerequisites before I can sit the exam?
Yes. The Academy states that to access a certification exam you must first complete the upstream certifications according to its prerequisite diagram. The ML Practitioner sits downstream of the Core Designer Certificate in that diagram, so plan to earn Core Designer first rather than booking the ML Practitioner exam directly.
Which courses should I take to prepare?
The Academy lists a dedicated ML Practitioner learning path for honing skills on Dataiku's visual tools for building machine learning models, alongside recommended courses including Machine Learning Basics, Scoring Basics, and Interactive Statistics. Working through the path in order gives you coverage of both exam domains before you attempt the assessment.
How much does the exam cost, and how long is the certificate valid?
The retrieved source material does not state an exam fee or a validity period for the ML Practitioner Certificate. Both values are therefore unconfirmed here. Check the official Dataiku Academy certification page for current pricing and any recertification requirements before you register.
What happens if I fail - can I retake it?
The source does not describe a retake policy, including any waiting period or attempt limit. Because this detail is unpublished in the material reviewed, confirm it directly with Dataiku Academy before scheduling. Do not assume a free immediate retake; plan to pass on your first attempt.
How should I split study time between the two domains?
The two domains - visual machine learning and interactive statistics - carry equal weight in this study outline. A sensible order is Machine Learning Basics, then Scoring Basics to consolidate the modelling workflow, then the Interactive Statistics course, since exploratory statistics supports feature understanding before modelling.
What are the most common ways candidates lose marks?
Weak spots tend to be the parts of the workflow people skip in practice: how models are trained and compared in the visual interface, how a model is deployed to score new data, and which visual statistics tool answers a given question. Hands-on repetition in a Dataiku instance beats reading slides.
Is this page an official Dataiku resource?
No. This is an independent study page written for candidates searching for exam information. It is not affiliated with, endorsed by, or produced by Dataiku. Certification names, durations, and prerequisites should always be verified against the official Dataiku Academy site, which is the authoritative source.