Designing and Implementing a Data Science Solution on Azure (DP-100T01)

 

Course Overview

DP-100 is an outstanding data science course that our students have found of great value.

It is important to reinforce however that this course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.

Before attending this course, students MUST have:

  • Deep experience in training, building, and evaluating machine learning models
  • A solid command of Python and its data science libraries including: pandas, scikit-learn, matplotlib, and seaborn.
  • Experience with statistical learning concepts such as: regression, correlation, normalization, feature importance, and AUC - ROC
  • Azure Fundamentals

Who should attend

This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.

Prerequisites

Before attending this course, students must have:

  • A 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.

Course Objectives

  • Introduction to Azure Machine Learning
  • No-Code Machine Learning with Designer
  • Running Experiments and Training Models
  • Working with Data
  • Compute Contexts
  • Orchestrating Operations with Pipelines
  • Deploying and Consuming Models
  • Training Optimal Models
  • Interpreting Models
  • Monitoring Models

Course Content

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 in Microsoft Azure.

Classroom training

Длительность 3 дня

Online training

Длительность 3 дня

 
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Russia

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RCIS
Online training Time zone: Eastern European Summer Time (EEST) Язык курса: pусский
Online training This is an pусский language FLEX course.
Time zone: Eastern European Summer Time (EEST)
Online training Time zone: Eastern European Summer Time (EEST) Язык курса: pусский

Fast Lane Flex™ Classroom If you can't find a suitable date, don't forget to check our world-wide FLEX training schedule.

Instructor-led Online Training:   This is an Instructor-Led Online course
FLEX тренинги проводятся в классе с возможностью присутствия дистанционных слушателей.