Program profile · official sources
Databricks Certified Machine Learning Professional
An enterprise-scale Databricks ML assessment for practitioners designing, implementing and managing production solutions.
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Who it is for
Practitioners managing enterprise-scale machine-learning solutions on Databricks are the audience.
Who should skip it
Compare the Associate exam if your objective is assessment of basic Databricks ML tasks rather than the enterprise-scale scope here.
Facts checked 6 Oct 2026
- Price
- USD 200
- (USD 200 for one attempt, plus applicable taxes as required per local law; optional preparation and repeat attempts are separate.)
Before tax.
- Provider link
See the official exam guide at Databricks ↗
Official site. No commission.
- Time
- 120 minutes for the exam assessment; not preparation time
- Level
- Professional
- Credential
- two years
Valid for two years; recertification requires taking the full currently live exam.
industry certification- Format
- Proctored certification exam
- Questions: 59 scored questions.
- Prerequisites
- No prerequisite required. Course attendance and one year of hands-on Databricks experience are highly recommended, plus Python, scikit-learn, SparkML, MLflow, Lakehouse Monitoring and Model Serving knowledge.
Sources ↗
- Price · https://www.databricks.com/sites/default/files/2025-10/databricks-certified-machine-learning-professional-exam-guide-september.pdf
- Duration · https://www.databricks.com/sites/default/files/2025-10/databricks-certified-machine-learning-professional-exam-guide-september.pdf
- Official program page · https://www.databricks.com/sites/default/files/2025-10/databricks-certified-machine-learning-professional-exam-guide-september.pdf
What you actually do
Scalable SparkML pipelines, distributed training, advanced MLflow, MLOps testing, automated retraining, Lakehouse Monitoring and serving define the assessed work. The online-proctored exam has 59 scored multiple-choice questions over 120 minutes. A year of hands-on experience and relevant tool knowledge are highly recommended; the provider nevertheless states that formal prerequisites are not required.
Use the enterprise-scale emphasis to decide whether this is the relevant assessment. Pipelines, distributed training, monitoring and serving address responsibilities that extend beyond basic model development. A person working on those operational systems may have a different goal from someone seeking a first check of Databricks ML skills. The Associate alternative is therefore a scope comparison, not simply a cheaper or easier substitute.
The experience recommendation needs the same care. A year of hands-on work describes the intended practical background, while the provider states that a formal prerequisite is not required. Those statements can coexist. They do not guarantee that every candidate without that background is ready, and they do not establish an additional eligibility test beyond the recorded conditions.
A useful preparation question is which operational tasks you have actually handled. Consider the named areas of testing, retraining, monitoring and model serving against your own experience. This is a way to identify learning needs, not a promise that one particular study route will produce a passing result.
Before you start
No prerequisite required. Course attendance and one year of hands-on Databricks experience are highly recommended, plus Python, scikit-learn, SparkML, MLflow, Lakehouse Monitoring and Model Serving knowledge.
Curriculum
Professional ML coverage concerns enterprise-scale tasks, not timed course units. The 120-minute examination length is not a preparation estimate, and the record supplies no passing threshold from which a study allocation could be inferred.
| Entry | Subject | Listed time | Share | Role | Observed |
|---|---|---|---|---|---|
| 1 | Model Development | Not stated | Not calculated | Exam section; covers scalable pipelines, distributed training, MLflow and feature engineering. | 2026-09-07 |
| 2 | MLOps | Not stated | Not calculated | Exam section; covers testing, environments, retraining and monitoring. | 2026-09-07 |
| 3 | Model Deployment | Not stated | Not calculated | Exam section; covers serving and rollout management. | 2026-09-07 |
US price
| Purchase information | Recorded terms |
|---|---|
| Access and billing | USD 200 for one attempt, plus applicable taxes as required per local law; optional preparation and repeat attempts are separate. Repeat-attempt cost is not established in the reviewed source. |
| Refund and retakes | Refund and retake terms are not established in these stored policy fields. |
Alternatives
The other assessments involve different cloud and ML-engineering contexts. Compare their platform-specific responsibilities, recommended background and current exam version before assuming equivalence from an ML title. The recorded fees concern examination attempts, while time spent preparing remains a separate commitment that these figures do not quantify. Use your actual production responsibilities to decide which assessment scope deserves closer comparison before booking an attempt.
Professional Machine Learning Engineer
| Provider and format | Level | Workload | Award | US price observation |
|---|---|---|---|---|
| Google Cloud · Proctored certification exam | Professional | 2 hours for the exam assessment; not preparation time | industry certification | USD 200. USD 200 for one certification exam registration/attempt. Optional preparation and repeat-attempt costs are separate. Currency is explicitly stated by the first-party Spanish localization. |
| Entry and assessment questions | Recorded answer |
|---|---|
| Who is it aimed at? | Professional ML engineers who build, evaluate, productionize and optimize conventional and generative-AI solutions on Google Cloud, with strong programming, data platform, distributed processing, model architecture, pipelines, MLOps and metrics skills. |
| What preparation is required? | None formally. Recommended: 3+ years of industry experience, including at least 1 year designing and managing solutions with Google Cloud. |
| How is the award earned? | Pass the certification exam; the reviewed sources do not state the passing-score threshold. |
Official source · 2026-10-03 | Official source · 2026-09-06
AWS Certified Machine Learning Engineer - Associate (MLA-C02, beta)
| Provider and format | Level | Workload | Award | US price observation |
|---|---|---|---|---|
| Amazon Web Services · Proctored certification exam, beta version (Pearson VUE testing center or online proctored) | Associate | Beta exam: 170 minutes for 85 questions; not preparation time | industry certification | USD 75. As shown in the United States on 4 October 2026, the AWS certification page lists the MLA-C02 beta exam at $75 USD, labelled beta pricing. The price for general availability is not stated; general availability registration and delivery dates are TBD. Tax treatment is not stated on the captured beta page; optional preparation is separate from the exam fee. |
| Entry and assessment questions | Recorded answer |
|---|---|
| Who is it aimed at? | ML engineers, MLOps and LLMOps engineers, data engineers, backend software developers and data scientists with at least 1 year of experience using Amazon SageMaker AI, Amazon Bedrock and other ML engineering AWS services. |
| What preparation is required? | No prerequisite certification is stated on the captured pages. The exam guide recommends at least 1 year of experience using Amazon SageMaker AI, Amazon Bedrock and other AWS services for ML engineering, plus at least 1 year in a related role, with experience in both traditional ML and generative AI. |
| How is the award earned? | Pass the exam. The exam guide gives a scaled score of 100 to 1,000 with a minimum passing score of 720 and a pass or fail designation that, per its note, does not apply to the beta version; beta results are typically available within 5 business days. |
| What remains unconfirmed? | Badge or sharing terms are not stated on the captured pages. |
Questions before enrolling
What passing and renewal requirements are established for the Professional credential?
The award title is Databricks Certified Machine Learning Professional, with issuer Databricks. Pass the certification exam; passing threshold not stated. Valid for two years; recertification requires taking the full currently live exam.
Change log
- : Initial recorded review of official exam, scope, price and credential facts. · Source
- : Price recheck: USD 200 plus applicable taxes as required per local law. Earlier 7 September 2026 record held tax basis unstated (null); fee amount remains USD 200. Other factual observation dates retained. · Source