The Databricks Machine Learning Associate tests building models on the Databricks platform (AutoML, MLflow, Unity Catalog, Spark ML), while the AWS Machine Learning Engineer Associate (MLA-C02) tests putting ML and generative AI into production on AWS with SageMaker AI and Amazon Bedrock. Pick the one that matches the platform your team runs on.
Last updated September 2026.
| Databricks ML Associate | AWS MLA-C02 | |
|---|---|---|
| Vendor platform | Databricks Data Intelligence Platform | AWS (SageMaker AI, Amazon Bedrock) |
| Cost | $200 USD (plus local tax) | $150 USD standard (beta priced lower) |
| Questions | 48 scored (unscored items may appear) | 65 (50 scored, 15 unscored) |
| Time limit | 90 minutes | 130 minutes |
| Passing score | Not published | 720 on a 100 to 1,000 scale |
| Question types | Multiple choice, multiple selection | Multiple choice, multiple response |
| Delivery | Online proctored | Pearson VUE test center or online proctored |
| Recommended experience | 6+ months hands-on | 1 year with SageMaker AI and Bedrock, plus 1 year in a related role |
| Validity | 2 years | 3 years |
| Generative AI in scope | No (covered by a separate GenAI Engineer exam) | Yes, in every domain |
From the official Databricks Machine Learning Associate exam guide (1 Mar 2025 edition) and the official MLA-C02 exam guide. Confirm prices at registration.
The guide lists 48 objectives across four sections and the exam has 48 scored questions, so it is roughly one question per objective. By objective count, Databricks Machine Learning is 38% (AutoML, Unity Catalog, MLflow tracking and the model lifecycle), Model Development 31% (training, tuning, Spark ML), Data Processing 19%, and Model Deployment only 12%. All ML code is Python. It is a platform exam: knowing ML in general is not enough without knowing how Databricks does it.
MLA-C02 weights its four domains 28/24/24/24, and Deployment plus Operating and Securing together are 48% of the exam. It asks you to choose inference options, autoscale endpoints, provision with infrastructure as code, run CI/CD with SageMaker Pipelines, monitor drift, and lock things down with IAM. The C02 version also brings foundation models, RAG, agents, and Bedrock Guardrails into scope, which the Databricks ML Associate leaves to its separate GenAI exam.
The short version: Databricks asks "can you build and track a good model here?", AWS asks "can you run one safely and cheaply in production?".
Your team trains models in Databricks notebooks, you track experiments in MLflow, and your features live in Unity Catalog. It is the smaller exam (90 minutes) and the most direct proof of platform fluency.
Your models ship on SageMaker AI endpoints or you build on Bedrock, and your role leans toward MLOps or ML engineering. It is the longer, broader exam and covers generative AI too.
If you work on both platforms, which is common when Databricks runs on AWS, take the exam that matches your current day job first. The overlap (evaluation metrics, tuning, the train, validate, test discipline) makes the second one easier. If generative AI is the reason you are looking, the Databricks counterpart is the Generative AI Engineer Associate, not the ML Associate.
The Databricks ML Associate is the shorter exam, with 48 scored questions in 90 minutes against 65 questions in 130 minutes for AWS MLA-C02. MLA-C02 is also broader, because it adds deployment infrastructure, security, and generative AI, so it usually needs the longer preparation.
Neither is better in general: pick the one that matches the platform your employer or target employers use. The Databricks ML Associate proves platform fluency with AutoML, MLflow, and Unity Catalog, while AWS MLA-C02 proves production ML engineering on SageMaker AI and Bedrock.
No. The Databricks Machine Learning Associate focuses on classic ML on the Databricks platform. Generative AI on Databricks is tested by the separate Databricks Generative AI Engineer Associate exam.
Databricks certifications, including the ML Associate, are valid for two years. AWS certifications, including the Machine Learning Engineer Associate, are valid for three years.
Certified has a Databricks ML Associate course mapped to the official objectives and a complete MLA-C02 course with seven practice exams.
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