Exam Name: Databricks Certified Machine Learning Professional
Certification Provider: Databricks
Corresponding Certification: ML Data Scientist
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Reference: https://www.databricks.com/learn/certification/machine-learning-professional
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Databricks Certified Machine Learning Professional Sample Questions:
A machine learning engineer wants to view all of the active MLflow Model Registry Webhooks for a specific model.
They are using the following code block:
Which of the following changes does the machine learning engineer need to make to this code block so it will successfully accomplish the task?
- A. Replace list with webhooks in the endpoint URL
- B. Replace list with view in the endpoint URL
- C. There are no necessary changes
- D. Replace POST with PUT in the call to http request
- E. Replace POST with GET in the call to http request
Correct Answer: E 🗳️
A Machine Learning Engineer needs to digitize millions of historical documents spanning 200+ years with vastly different handwriting styles, fonts, languages, document conditions, and paper types. To do this, the engineer wants to train thousands of specialized OCR models to extract text. The number of documents vary significantly. They need an efficient approach for this parallel model training task. Which approach suits their needs?
- A. Use Ray map_in_batches to allocate resources based on the various sizes of models and data volumes.
- B. Use Spark for data preprocessing and orchestrate parallel model training jobs through Databricks workflows.
- C. Use Scikit-learn's ML library within a Pandas UDF to parallelize training across data partitions.
Use groupby.applyInPandas. - D. Use Spark MLlib with custom Spark UDFs to distribute across partitions.
Correct Answer: A 🗳️
Explanation: Only visible for 2Pass4sure members. You can sign-up / login (it's free).
A data scientist has developed a model model and computed the RMSE of the model on the test set. They have assigned this value to the variable rmse. They now want to manually store the RMSE value with the MLflow run.
They write the following incomplete code block:
Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?
- A. log_param
- B. log_artifact
- C. log_model
- D. There is no way to store values like this.
- E. log_metric
Correct Answer: B 🗳️
A Data Scientist is building a propensity model for an e-commerce start-up. The company maintains 7GB of historical data and receives about 5MB of new transaction data daily. The goal is to generate daily purchase predictions for all users by 7:00 AM each morning. As the start-up is in its early stages, the data scientist must prioritize a highly cost-efficient approach. Which approach should the Data Scientist take?
- A. Use a single-node compute to build a model with libraries like scikit-learn. The model can then be integrated into an always-on streaming pipeline, to ensure immediate processing of incoming data in order to meet the SLA.
- B. Use a single-node compute to build a model with libraries like scikit-learn. The model can then be deployed as an always-on REST API so that users can query the API to get the predictions whenever they want.
- C. Use a multi-node compute and leverage distributed frameworks like SparkML to train the model.
The model can then be scheduled as a nightly batch job that runs on a multi-node compute. - D. Use a single-node memory compute to build a model with libraries like scikit-learn. The model can then be scheduled as a nightly batch job that runs on a single-node compute.
Correct Answer: D 🗳️
Explanation: Only visible for 2Pass4sure members. You can sign-up / login (it's free).
A Machine Learning Engineer needs to build a credit risk model using Databricks. Due to strict data governance, production data cannot be accessed from development or staging environments. To manage MLOps, the engineer uses a "deploy code" strategy with separate development, staging, and production environments mapped to different catalogs in Unity Catalog. The CI/CD pipeline automates environment transitions. What is the primary architectural component promoted from staging to production to generate the final, production-ready model in this scenario?
- A. The model version entry in the Unity Catalog that has been transitioned from the "Staging" to the
"Production" alias. - B. The CI/CD-approved model training source code, which will be executed in the production environment on the full production dataset.
- C. The model artifact trained and validated in the staging environment on a subset of the data.
- D. A containerized image of the complete inference pipeline, including feature transformations.
Correct Answer: B 🗳️
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