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Learn to Design and Implement a Data Science Solution on Azure. In this 4-day instructor-led course participants learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.

Data Scientist is the central role in developing machine learning models. This role is responsible for solving the business problem that initiated the project. While the Data Engineer will prepare the data to be used for the models, the Data Scientist determines what data is needed for model training, creates model features from the data, determines what machine learning model to use, trains and evaluates the model, and often has involvement in model deployment. Often the data scientist needs to evaluate multiple models to determine which performs the best. Note: before attending this course, students must have:

  • Azure Fundamentals
  • Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one
  • How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib and seaborn

Target Audience
This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.

Related Links: Microsoft Certified: Azure Data Scientist Associate

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  • Course Number DP-100
  • Course Length 4 days
  • Course Fee $2,295.00
  • Delivery Format VLT (Instructor Led; Virtual LIVE Online; Remote Training)
  • Course Topic Business Intelligence
  • Vendor Microsoft
  • Technology Azure
Need a different date? This course is also offered on these dates

About the instructorPeter Avila

Microsoft Certified Trainer

Peter is a consultant specializing in the design and development of database systems using SQL Server and .Net technologies. Peter has operated a nation-wide consulting business since 1991. He was a course designer and instructor of database and software development technologies at Harvard University; UC Berkeley, and the Worcester Polytechnic Institute, and he is author of “An Intuitive Approach to Database Design; An Introduction to Data Modeling.”

Peter uses an intuitive approach to learning that applies the way we all learn in the real world and gives students experiences on which to draw when they’re back on the job applying their new skills. “Learning is the most fun, satisfying, and enduring when we have our own empirical experiences – our own AHA! moment when we experience a discovery. The classroom offers a great opportunity to create those moments in a fun and focused environment. It’s great when students tell me that the experience they had in the classroom is what allowed them to finally understand a topic and solve a tough problem at work.”

Training Location

Designing and Implementing a Data Science Solution on Azure (DP-100)

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