DP-100: Microsoft Azure Data Scientist

In this 4-day training, you will learn how to design and implement Data Science Solutions and operate machine learning workloads at cloud scale using Azure Machine Learning.

The course will teach you how to manage Azure resources for machine learning, upload and prepare datasets for training, run experiments, train predictive models, manage and deploy machine learning models in production, and monitor cloud resource usage. Everything you need to become a Microsoft Azure Data Scientist!

This training prepares you for the Azure Data Scientist exam and certification.

Here’s What You’ll Get

Training Manual
Hands-On Lab
Cloud Credit
Private Slack Channel
Unlimited Teams Calls
Exam Voucher
Certificate of Completion
Self-Paced or Classroom Training
180-day Lab Access

Training Details

This training will provide you the knowledge and skills to design and implement Data Science Solutions for the Microsoft Azure environment. 

You will learn how to manage Azure resources for machine learning, upload and prepare datasets for training, run experiments and train models. In addition, I’ll teach you to deploy and operationalize machine learning solutions in production, implement responsible AI… and much more!

The training combines lectures with lab exercises to help you understand the contents. As part of this training, you´ll receive an Azure Pass with credits to spend on your own cloud services. The pass is valid for 30 days.

 

 

Name: DP-100 Microsoft Azure Data Scientist.

Format: Classroom.

Content: training manual, case studies, lab exercises, Azure cloud credit, practice exam, and an exam voucher.

Requirements: a laptop with a web browser installed. Chrome or Edge is recommended. Students must have knowledge and experience in data science and machine learning.

Support: Live classroom support.

Associated certification: Microsoft Azure Data Scientist.

 

Training Curriculum

Introduction

Course Intro: About this course

Getting Started with Azure Machine Learning

Introduction

Working with Azure Machine Learning

Knowledge Check

Lab Exercises

Create an Azure Machine Learning Workspace

Visual Tools for Machine Learning

Introduction

Automated Machine Learning

Azure Machine Learning Designer

Knowledge Check

Lab Exercises

Use Automated Machine Learning

Use Azure Machine Learning Designer

Running Experiments and Training Models

Introduction

Training and Registering Models

Knowledge Check

Lab Exercises

Run Experiments

Train Models

Working with Data

Introduction

Working with Datastores

Working with Datasets

Knowledge Check

Lab Exercises

Work with Data

Working with Compute

Introduction

Environments

Compute Targets

Knowledge Check

Lab Exercises

Work with Compute

Orchestrating Machine Learning Workflows

Introduction to Pipelines

Publishing and Running Pipelines

Knowledge Check

Lab Exercises

Create a Pipeline 

Deploying and Consuming Models

Introduction 

Real-Time Inferencing

Batch Inferencing

Continuous Integration and Delivery

Knowledge Check

Lab Exercises

Create a Real-Time Inference Service

Create a Batch Inference Service

Training Optimal Models

Introduction

Hyperparameter Tuning

Automated Machine Learning

Knowledge Check

Lab Exercises

Tune Hyperparameters

Use Automated Machine Learning from the SDK

Responsible Machine Learning

Introduction

Differential Privacy

Model Interpretability

Fairness

Knowledge Check

Lab Exercises

Explore Differential Privacy

Interpret Models

Detect and Mitigate Unfairness

Monitoring Models

Introduction

Monitoring Models with Application Insights

Monitoring Data Drift

Knowledge Check

Lab Exercises

Monitor a Model

Monitor Data Drift

Book a Classroom Training

Classroom trainings are conducted during business hours and hosted online or on-site at your place of work. All students need to participate is a laptop, a web browser, and Microsoft Teams.

Please use the form below to book a call with me to set up your classroom training. We’ll discuss your business requirements, team size, and preferred location of the training (online or on-site) and make sure you get what you need. A typical classroom training can usually be scheduled within 30 days and can accomodate up to 15 people on-site and 30 people online.

Looking For Something Else?

CHECK OUT MY OTHER AI TRAINING

Is this training course not exactly what you’re looking for? No problem, I have many other AI and Data Science training courses in my catalog. Take a look at these alternatives.

“Finally finished this course. Would totally recommend. Thanks Mark!’

Chibuike Kenneth, online student