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DP-100: Designing and Implementing a Data Science solution on Azure
Minimum cohort size: 10 learners
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Course
DP-100: Designing and Implementing a Data Science solution on Azure
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. Leverage your existing knowledge of Python for machine learning in Microsoft Azure.
Benefit from instructor-led preparation for the DP-100 certification exam with tips, tricks, guidance, and mentored support.
Online Live Classes
Intermediate Level
Mentor Support
DP-100 is a four-day course for data scientists who want to build and operate machine learning solutions in the cloud using Azure Machine Learning.
This DP-100 training introduces you to Azure Machine Learning, Automated Machine Learning, and Designer Visual Tools for trainiing, evaluating, and deploying machine learning models without writing any code. You will discover how to run code-based experiments. Plus, you will explore how to create and manage datastores, datasets, environments and computer targets. For effective Machine Learning Operationalization (ML Ops) solutions you will understand how to create, publish, and run pipelines to automate machine learning workflows. You will be guided on how to deploy, consume, monitor, and optimize the models. Plus, you will explore the techniques for applying responsible machine learning to maintain privacy and transparency.
This DP-100 training introduces you to Azure Machine Learning, Automated Machine Learning, and Designer Visual Tools for trainiing, evaluating, and deploying machine learning models without writing any code. You will discover how to run code-based experiments. Plus, you will explore how to create and manage datastores, datasets, environments and computer targets. For effective Machine Learning Operationalization (ML Ops) solutions you will understand how to create, publish, and run pipelines to automate machine learning workflows. You will be guided on how to deploy, consume, monitor, and optimize the models. Plus, you will explore the techniques for applying responsible machine learning to maintain privacy and transparency.
This course will prepare you for taking the DP-100: Designing and Implementing a Data Science Solution on Azure certification exam. Entry for the exam is not included. However, you will get a clear overview of the Microsoft certification process, plus you will get tips and tricks, testing strategies, practice questions, and useful information to help you pass the exam successfully.
This course comprises 19 purposely designed modules that take you on a carefully defined learning journey.It is an instructor-led course which runs to a fixed schedule, with set start and finish dates. It is driven forward by your instructor and features live sessions that are aired at a set time. You will, however, have time to complete certain activities at your own pace outside of the live sessions.The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs and online exams questions.As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.
Once you have successfully completed the course, you will earn your Certificate of Completion.
You will be able to:Design and prepare a machine learning solution Explore data and train models Prepare a model for deployment Deploy and retrain a model
You must be able to:Create cloud resources in Microsoft Azure. Use Python to explore and visualize data. Train and validate machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Work with containers.
This course will help you to prepare for the DP-100: Designing and Implementing a Data Science Solution on Azure certification exam.
It is ideal 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.When you take this course, you will also get information and guidance on the Microsoft certification process, knowledge checks and practice questions, and useful tips on how to pass the exam.
Course Outline
Introduction
Grading Scheme
Pre-Requisite
Exam and Certification Details
About this module
Identify your data source and format
Choose how to serve data to machine learning workflows
Design a data ingestion solution
Knowledge Check
About this Module
Identify machine learning tasks
Choose a service to train a machine learning model
Decide between compute options
Knowledge Check
About this Module
Understand how model will be consumed
Decide on real-time or batch deployment
Knowledge Check
About this Module
Explore an MLOps architecture
Design for monitoring
Design for retraining
Knowledge Check
About this Module
Create an Azure Machine Learning workspace
Identify Azure Machine Learning resources
Identify Azure Machine Learning assets
Train models in the workspace
Knowledge Check
About this Module
Explore the studio
Explore the Python SDK
Explore the CLI
Knowledge Check
About this Module
Understand URIs
Create a datastore
Create a data asset
Knowledge Check
About this Module
Choose the appropriate compute target
Create and use a compute instance
Create and use a compute cluster
Knowledge Check
About this Module
Understand environments
Explore and use curated environments
Create and use custom environments
Knowledge Check
About this Module
Preprocess data and configure featurization
Run an Automated Machine Learning experiment
Evaluate and compare models
Knowledge Check
About this Module
Configure MLflow for model tracking in notebooks
Train and track models in notebooks
Knowledge Check
About this Module
Convert a notebook to a script
Run a script as a command job
Use parameters in a command job
Knowledge Check
About this Module
Track metrics with MLflow
View metrics and evaluate models
Knowledge Check
About this Module
Define a search space
Configure a sampling method
Configure early termination
Use a sweep job for hyperparameter tuning
Knowledge Check
About this Module
Create components
Create a pipeline
Run a pipeline job
Knowledge Check
About this Module
Log models with MLflow
Understand the MLflow model format
Register an MLflow model
Knowledge Check
About this Module
Understand Responsible AI
Create the Responsible AI dashboard
Evaluate the Responsible AI dashboard
Knowledge Check
About this Module
Explore managed online endpoints
Deploy your MLflow model to a managed online endpoint
Deploy a model to a managed online endpoint
Test managed online endpoints
Knowledge Check
About this Module
Understand and create batch endpoints
Deploy your MLflow model to a batch endpoint
Deploy a custom model to a batch endpoint
Invoke and troubleshoot batch endpoints
Knowledge Check
Instructions
Explore developer tools for workspace interaction
Explore the Azure Machine Learning workspace
Make data available in Azure Machine Learning
Work with compute resources in Azure Machine Learning
Work with environments in Azure Machine Learning
Train a model with the Azure Machine Learning Designer
Find the best classification model with Automated Machine Learning
Track model training in notebooks with MLflow
Run a training script as a command job in Azure Machine Learning
Use MLflow to track training jobs
Perform hyperparameter tuning with a sweep job
Run pipelines in Azure Machine Learning
Compare and evaluate models
Log and register models with MLflow
Deploy a model to a batch endpoint
Deploy a model to a managed online endpoint
Practice Set 1
Practice Set 2
DP-100 Project
Download your certificate
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FAQs
You first need to complete the recommended training for DP-100 with a Microsoft authorized training partner. SKillUp Online is a Microsoft authorized training partner.
Once you have completed your training, visit Microsoft's official website. Then, register for the Designing and Implementing a Data Science Solution on Azure exam, and schedule it with Pearson VUE. Take the exam, pass it, and get certified!
It is recommended that learners have fundamental knowledge of cloud computing concepts, and experience in general data science and machine learning tools and techniques.
It is mandatory to complete the Microsoft Azure AI Fundamentals course before taking the DP-100 course.
DP-100 certification leverages your existing knowledge of Python and machine learning. Upon completion of this course, you will be able to showcase your talent in operating with a multidisciplinary team to train, analyze, and readying of AI models to resolve business issues.
Also, the DP-100 certification will help you develop skills in numerous ways and best practices associated with Azure data science and machine learning services.
This DP-100 online training will explain the concepts required to prepare you for the DP-100: Designing and Implementing a Data Science Solution on Azure exam.
DP-100 certification is ideal for data science professionals who have prior knowledge of Python as well as machine learning frameworks. This course will prepare you for the role of data scientist. Moreover, DP-100 exam will also prepare you for taking Associate level courses in the future.
If you sign up with SkillUp Online, our Microsoft Certified Trainers (MCTs) will walk you through all the modules as per the Microsoft Official Curriculum (MOC) once the course starts. You do not need to prepare anything in advance.
Type of certificate
Certificate of completion
About this course
19 Modules
18 Skills
Includes
Discussion space
19 Knowledge checks
02 Practice exam
16 Labs
01 Project
Create
Virtual machine
Azure Machine Learning Workspace
Datastores
Datasets
Compute targets
Pipelines
Real-time Inferencing Service
Batch Inferencing Service
Exercises to explore
Use Automated Machine Learning
Use Azure Machine Learning Designer
Train models
Work with data and compute
Explore differential privacy
Detect and mitigate unfairness
Monitor a model with application insights
You’ll learn with these experts
Microsoft
This course is led by experienced Microsoft Certified Trainers (MCTs).
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