DP-3014: Implementing a Machine Learning solution with Azure Databricks
Note: There is currently no assessment for this course
This course is designed for data scientists and machine learning engineers who want to implement machine learning solutions using Azure Databricks, a powerful cloud platform for data analytics and machine learning. Participants should have prior experience with Python and familiarity with popular machine learning frameworks such as Scikit-Learn, PyTorch, and TensorFlow.
Throughout the course, learners will explore the capabilities of Azure Databricks, including how to use Apache Spark for data transformation and analysis. They will gain hands-on experience in training machine learning models, managing the machine learning lifecycle with MLflow, and optimizing model performance through hyperparameter tuning. The course also covers the use of AutoML for simplifying model building and deep learning techniques for complex tasks. Additionally, participants will learn how to effectively manage machine learning models in production, ensuring they can deliver real-time insights and support data-driven decision-making.
By the end of this course, participants will have the skills needed to leverage Azure Databricks for scalable machine learning solutions, enhancing their ability to collaborate effectively in data-driven environments.