Databricks-ML-Assoc Databricks Machine Learning Practice Question
A data scientist wants to track the performance of a model training run in Databricks. They use MLflow to log parameters and metrics. After the run, they need to view all runs for the experiment in a web-based interface. Which URL should they navigate to?
⚠ Common exam trap
Many candidates confuse the MLflow experiments UI with other Databricks workspace URLs like jobs or notebooks, which serve different purposes.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
https://<databricks-instance>/#mlflow/experiments/<experiment_id>
The MLflow experiments UI is accessed via the '#mlflow/experiments/<experiment_id>' URL. This interface displays all runs for the experiment, including logged parameters, metrics, and artifacts, enabling comparison and analysis of model training results.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
https://<databricks-instance>/#job/<job_id>
Why it's wrong here
The '#job/<job_id>' URL points to a specific job's details page in Databricks, not to MLflow experiments. Jobs are used to schedule and run notebooks or libraries, but they do not provide the MLflow run comparison interface. This URL would not show the experiment's runs.
- ✗
https://<databricks-instance>/#setting/account
Why it's wrong here
The '#setting/account' URL leads to account settings, where you can manage users, groups, and other administrative configurations. It does not provide access to MLflow experiments or runs. This URL is unrelated to model tracking and would not show any experiment data.
- ✓
https://<databricks-instance>/#mlflow/experiments/<experiment_id>
Why this is correct
The MLflow experiments UI in Databricks is accessible at the URL pattern '#mlflow/experiments/<experiment_id>'. This page lists all runs for the specified experiment, allowing you to compare metrics, parameters, and artifacts. It is the standard way to view experiment results in the Databricks workspace.
- ✗
https://<databricks-instance>/#notebook/<notebook_id>
Why it's wrong here
The '#notebook/<notebook_id>' URL opens a specific notebook in the workspace. While notebooks can contain MLflow tracking code, this URL does not display the experiment's runs or metrics. It is used for editing and running notebook code, not for viewing MLflow experiment results.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-ML-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-ML-Assoc exam.