Whether you are starting your AI engineering journey or expanding your existing skills, MammothClub offers a practical catalog of courses, paths, and focused learning opportunities.
Test your knowledge and prepare for the certification exam with these comprehensive mock exam questions!
Test your knowledge and prepare for the certification exam with these comprehensive mock exam questions!
Test your knowledge and prepare for the certification exam with these comprehensive mock exam questions!
Test your knowledge and prepare for the certification exam with these comprehensive mock exam questions!
Test your knowledge and prepare for the certification exam with these comprehensive mock exam questions!
Test your knowledge with 50+ questions from the Experimentation section of the Databricks Certified Machine Learning Professional certification. Find out if you’re ready to ace the exam — if you can manually log parameters, models, and evaluation metrics using MLflow, programmatically access and use data, metadata, and models from MLflow experiments, and perform experiment tracking workflows with model signatures and input examples.
Test your knowledge with 50+ questions from the Model Lifecycle Management section of the Databricks Certified Machine Learning Professional certification. Find out if you’re ready to ace the exam — can you describe an MLflow flavor and the benefits of using MLflow flavors, explain the advantages of using the pyfunc MLflow flavor, understand the process and benefits of including preprocessing logic and context in custom model classes and objects, describe the basic purpose and user interactions with the Model Registry, and programmatically register a new model or a new model version?
Test your knowledge with 50+ questions from the Model Lifecycle Management section of the Databricks Certified Machine Learning Professional certification. Find out if you’re ready to ace the exam — can you add metadata to a registered model and its versions, identify, compare, and contrast the available model stages, transition, archive, and delete model versions, implement automated testing in ML Continuous Integration and Continuous Delivery (CI/CD) pipelines, and automate the model lifecycle using Model Registry webhooks and Databricks Jobs?
Dive into a preparatory course with videos, text aids and fun interactive exercises!
