There is a manual model option in DataRobot Python API. You can select it using the mode parameter in project.set_target (API Link - set_target ). This command will create blueprints from different model types (elastic net, xgboost etc specific to your dataset) and store them in the repository. You can then access all of the generated blueprints from the repository using get_blueprints function and run only the ones that you need.
Also, there is a Quick mode option in set_target where DataRobot will automatically run the most relevant blueprints for a particular dataset. This is optimized to give maximum accuracy without going through the whole autopilot process.
Hi FranksT, as my colleague Kreshnaa suggested a manual run of the dataset with the target selected will shortlist the Blueprints (BP) in the Repository. You could then do a text search of only those BPs with "Elastic-Net" in their titles to run from there. This topic and many others are covered in the DataRobot API classes for Python and R and you could probably clarify further with the instructors in the courses: