After this day you can train machine learning models directly in Azure Databricks and record every attempt with MLflow. You prepare data with Spark, tune hyperparameters automatically, try AutoML as a shortcut and know how a model moves from a notebook into production. The course is aimed at data scientists and AI engineers who already use Python and common ML libraries and want to move their work onto a scalable platform with proper tracking.
What you’ll take away.
- Prepare and explore data in Azure Databricks with Apache Spark
- Train models with common frameworks and log them traceably with MLflow
- Tune hyperparameters automatically and use AutoML for a first model candidate
- Train deep learning models on Databricks clusters
- Manage and deploy models for production use
Your training in detail
- Who is it for?
- Data scientists and AI engineers who want to train, compare and manage machine learning models on Azure Databricks.
- Prerequisites
- You explore data with Python and have already trained models with libraries such as scikit-learn, PyTorch or TensorFlow. No prior Databricks knowledge is needed.
- Format & planning
- Standard length: 1 training day. A different length can be arranged for companies.
Agenda: from understanding to application
Our independently developed agenda proposal. Focus areas, lab environment and scope are agreed before booking.
Azure Databricks overview: workspace, clusters and notebooks
Loading, transforming and visualising data with Apache Spark
Training and evaluating models
Tracking experiments, runs and models with MLflow
Hyperparameter tuning with Optuna and AutoML in Azure Databricks
Deep learning on Databricks and managing models in production
You train several model variants on a sample dataset, compare them in MLflow, improve the best one through hyperparameter tuning and register it for deployment.
Exams, licences & credentials
There is no Microsoft exam for DP-3014, so the course ends without a certification exam. It is not an official Microsoft course unless the offer explicitly says so.
Vendor references & review date
Sources checked on 2026-11-10. These sources describe the technology or external exam requirements. They do not imply a partnership with NextNowa.
Your learning content
These objectives describe the training topic. The specific syllabus, dates and trainer are agreed before booking; the written offer is binding.
Frequently asked questions
Do I need prior Databricks knowledge?
No. The course starts with the workspace, clusters and notebooks. You should, however, bring experience with Python and model training.
What role does MLflow play in the course?
MLflow is built into Azure Databricks. In the course you use it to record the parameters, metrics and models of each training run and to manage models for deployment.
Does DP-3014 Build machine learning solutions using Azure Databricks: ML models with Spark and MLflow include a certificate?
There is no Microsoft exam for DP-3014, so the course ends without a certification exam. It is not an official Microsoft course unless the offer explicitly says so.