Dp100 - SiteCrazyTechLabs

Course Description

Through this training, it is possible to acquire the necessary knowledge of Azure services to develop, train and deploy Machine Learning solutions.

The course starts with an overview of the Azure services that support data science. From there, it focuses on using Azure's premier data science service, the Azure Machine Learning service, to automate the data pipeline and data science. This course focuses on Azure and does not teach the student to perform data science. It is assumed that students already know this.

Information

Certification: Official Microsoft Certification
Prerequisites: Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Forming and validating machine learning models using common frameworks such as Scikit-Learn, PyTorch, and TensorFlow.
Modality: Distance Learning with online class
Support Material: Official material provided by Microsoft in English
Workload: 3 days
Skills: Intermediate Data Scientist Azure AI Engineer

Training information

Target Audience

This course is intended for Data Scientists and people with responsibilities administrative skills in training and implementing learning models for machine

Prerequisites

Successful Azure Data Scientists start this role with a fundamental knowledge of cloud computing concepts, and experience in general data science and machine learning tools and techniques.
Specifically:

Building cloud resources on Microsoft Azure.
Using Python to explore and visualize data.
Formation and validation of machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.

Set up an Azure Machine Learning workspace
- Create an Azure Machine Learning workspace
- Manage data object in Azure Machine Learning workspace
- Managing experiments in the computing context
Perform experiments and train models
- Create models using Azure Machine Learning Designer
- Run training scripts
- Generate metrics from the experiments run
- Automate training process templates
Optimize and manage templates
- Use Automated ML to create great models
- Use explainers to interpret the models
- Use Hyperdrive to adjust hyperparameters
- Manage Templates
Deploy and consume models
- Create production compute targets
- Deploy a template as a service
- Create pipelines for batch inference
- Publish a Pipeline Designer with a web service.

For more information about the official syllabus, visit the course page on Microsoft website:

Curso DP-100T01-A: Designing and Implementing a Data Science Solution on Azure

Instrutor

Jorge Maia

Jorge Maia, Computer Scientist, Master in Mechatronic Systems, PhD student in Systems Mechatronics, awarded in recent years by Microsoft for its performance in the technology community, is also Microsoft Certified Trainer and Microsoft MCT Regional Lead for Brazil, currently works as chief architect for cloud and Internet of Things projects at Crazytechlabs, Brazilian company with headquarters in Brasília and São Paulo, with national and international operations in the verticals retail, industry and engineering.

Since 2014, he has been dedicating himself exclusively to the Internet of Things and the use of cloud computing, topics that are always present in your podcast, articles and Youtube channel. Acting with education from the beginning of the 2000s, provides official Microsoft and personalized training for industries and companies in Brazil and abroad, he is currently a postgraduate professor at FIAP in systems architecture and Internet of Things courses, having already participated in other institutions higher education in recent years.