This briefing is designed for data scientists with existing knowledge of Python and machine learning frameworks, who want to build and operate machine learning solutions in the cloud.
DP-100 Designing and Implementing a Data Science Solution on Azure
Before attending this briefing, students must have:
Fundamental knowledge of Microsoft Azure
Experience of writing Python code to work with data, using libraries such as Numpy, Pandas, and Matplotlib.
Understanding of data science; including how to prepare data, and train machine learning models using common machine learning libraries such as Scikit-Learn, PyTorch, or Tensorflow.
Module 1: Introduction to Azure Machine Learning
Module 2: No-Code Machine Learning with Designer
Module 3: Running Experiments and Training Models
Module 4: Working with Data
Module 5: Compute Contexts
Module 6: Orchestrating Operations with Pipelines
Module 7: Deploying and Consuming Models
Module 8: Training Optimal Models
Module 9: Interpreting Models
Module 10: Monitoring Models
NOTE: Please contact us for group discounts and flexible scheduling for all of our workshops to meet your requirements.