DP-100T01: Designing And Implementing A Data Science Solution On Azure
Discover the Microsoft Certified: Azure Data Scientist Associate credential.
In today's fast-paced IT industry, what is one of the hottest roles? You'd be correct if you said data scientist. These professionals are in high demand, thanks to AI, machine learning, and data science.
A data scientist assists their company in visualizing and delivering innovation, improving customer experience, increasing revenue, and staying competitive. A data scientist, for example, supports a data-driven culture by employing rigorous scientific methodology and algorithms to uncover and solve business challenges as well as chase possibilities to help their firm achieve its objectives. We have the certification for you if this describes you, your skill set, and your enthusiasm for data.
Explore our top picks for Microsoft Azure certification courses for 2023.
Training Duration: 4 Days
- Certificate Of Completion Available
- Group Private Class
- VILT Class Available
- SBL-Khas Claimable
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.
- Manage Azure resources for machine learning
- Run experiments and train models
- Deploy and operationalize machine learning solutions
- Implement responsible machine learning
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:
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Creating cloud resources in Microsoft Azure.
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Using Python to explore and visualize data.
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Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
Working with containers to gain these prerequisite skills, take the following free online training before attending the course:
- Explore Microsoft cloud concepts.
- Create machine learning models.
- Administer containers in Azure
If you are completely new to data science and machine learning, please complete the following courses:
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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.
Module 1: Design A Machine Learning Solution
There are many options on Azure to train and consume machine learning models. Which service best fits your scenario can depend on a myriad of factors. Learn how to identify important requirements and when to use which service when you want to use machine learning models.- Design a data ingestion strategy for machine learning projects.
- Design a machine learning model training solution.
- Design a model deployment solution.
- Design a machine learning operation solution.
Module 2: Explore and configure the Azure Machine Learning workspace.
Throughout this learning path you explore and configure the Azure Machine Learning workspace. Learn how you can create a workspace and what you can do with it. Explore the various developer tools you can use to interact with the workspace. Configure the workspace for machine learning workloads by creating data assets and compute resources. This learning path helps prepare you for Exam DP-100: Designing and Implementing a Data Science Solution on Azure.- Explore Azure Machine Learning workspace resources and assets.
- Explore developer tools for workspace interaction.
- Make data available in Azure Machine Learning
- Work with compute targets in Azure Machine Learning
- Work with environments in Azure Machine Learning
Module 3: Work with data in Azure Machine Learning
Learn how to work with data in Azure Machine Learning. Whether you want to access data in notebooks or scripts, you can read data directly, through datastores, or data assets.- Make data available in Azure Machine Learning
Module 4: Experiment with Azure Machine Learning
Learn how to find the best model with automated machine learning (AutoML) and by experimenting in notebooks. This learning path helps prepare you for Exam DP-100: Designing and Implementing a Data Science Solution on Azure.- Find the best classification model with Automated MachineLearning
- Track model training in Jupyter notebooks with MLflow.
Module 5: Use notebooks for experimentation in Azure Machine Learning
Learn how to use Azure Machine Learning notebooks for experimentation. Similar to Jupyter, the notebooks are ideal for exploring your data and developing a machine learning model.- Track model training in Jupyter notebooks with MLflow.
Module 6: Train models with scripts in Azure Machine Learning
To prepare your machine learning workloads for production, you'll work with scripts. Learn how to train models with scripts in Azure Machine Learning. This learning path helps prepare you for Exam DP-100: Designing and Implementing a Data Science Solution on Azure.- Run a training script as a command job in Azure MachineLearning
- Track model training with MLflow in jobs.
- Perform hyperparameter tuning with Azure Machine Learning
Module 7: Optimize model training with Azure Machine Learning
Learn how to optimize model training in Azure Machine Learning by using scripts, jobs, components and pipelines.- Run a training script as a command job in Azure MachineLearning
- Track model training with MLflow in jobs.
- Perform hyperparameter tuning with Azure Machine Learning
- Run pipelines in Azure Machine Learning
Module 8: Manage and review models in Azure Machine Learning
Learn how to manage and review models in Azure Machine Learning by using MLflow to store your model files and using responsible AI features to evaluate your models.- Register an MLflow model in Azure Machine Learning
- Create and explore the Responsible AI dashboard for a model in Azure Machine Learning
Module 9: Deploy and consume models with Azure Machine Learning
Learn how to deploy a model to an endpoint. When you deploy a model, you can get real-time or batch predictions by calling the endpoint. This learning path helps prepare you for Exam DP-100: Designing and Implementing a Data Science Solution on Azure.- Deploy a model to a managed online endpoint.
- Deploy a model to a batch endpoint.
Propel your IT career to new heights with Microsoft certifications.
According to Pearson VUE's 2021 Value of IT Certification Survey, investing in Microsoft Certifications can accelerate your professional growth, enhance your skills, and boost your earning potential.
Join the thousands of IT professionals who have unlocked a world of opportunities by validating their expertise in cutting-edge Microsoft technologies with these recommended role-based certifications:
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DP-420T00: Designing & Implementing Cloud-Native Applications Using Cosmos DB
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The DP-100T01: Designing and Implementing a Data Science Solution on Azure course prepares learners for the Microsoft Certified: Azure Data Scientist Associate certification.
The DP-100 exam measures your ability to accomplish the following technical tasks: manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions; and implement responsible machine learning.
Skills measured
- Manage Azure resources for machine learning (25–30%)
- Run experiments and train models (20–25%)
- Deploy and operationalize machine learning solutions (35–40%)
- Implement responsible machine learning (5–10%)
Top Data Analyst Certifications for 2023
If you fit the profile of someone who loves to analyze data and discover insights and have fundamental understanding of data repositories and data processes, both on-premises and in the cloud, read on!
Is the Microsoft Certified: Azure Data Scientist Associate certification worth it?
Microsoft Certified: Azure Data Scientist Associate certification is worth considering for professionals looking to advance their career in data science and analytics within the Microsoft Azure ecosystem. This certification validates your knowledge and skills in using Azure tools and services to design, build, and deploy machine learning models and derive insights from data.
Furthermore, this Azure Data Science credential can be a valuable addition to your professional credentials, providing you with the knowledge and skills to excel in the growing field of data science and analytics within the Azure cloud platform.
Are Microsoft certifications worth it?
In today's fast-paced and highly competitive world of technology, it's more important than ever to stay ahead of the curve and differentiate yourself as a skilled professional.
Microsoft certifications are globally recognized, industry-standard credentials that showcase your expertise in various Microsoft technologies, making them a worthwhile investment in your career growth. By obtaining a Microsoft certification, you're not only validating your skills and knowledge, but also demonstrating your commitment to continuous learning and staying current with the latest industry trends.
Microsoft certifications cater to a wide range of roles, including developers, administrators, data professionals, and IT managers, providing a versatile pathway to career advancement. As organizations increasingly rely on Microsoft technologies such as Azure, Office 365, and Dynamics 365, the demand for certified professionals continues to grow. A Microsoft certification not only improves your employability, but also enhances your earning potential and credibility within your field.
Additionally, as a certified Microsoft professional, you gain access to exclusive resources, networking opportunities, and events, further elevating your career. Invest in your future by pursuing Microsoft certifications and unlock a world of opportunities, growth, and success in the ever-evolving technology landscape.
Why learn Azure?
In today's digital landscape, cloud computing has become an essential part of every organization's IT strategy, and Microsoft Azure stands at the forefront of this transformation. As one of the leading cloud platforms, Azure offers a wide range of services and tools, making it a highly sought-after skill for IT professionals across various industries.
By learning Azure, you're not only staying current with the latest developments in cloud technology but also empowering yourself to work on cutting-edge projects, improve your problem-solving capabilities, and drive innovation within your organization.
Azure's extensive range of services, such as Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS), provides a comprehensive and flexible environment for businesses to scale and adapt to evolving market demands.
As an Azure professional, you'll be equipped to deploy, manage, and maintain cloud infrastructure, ensuring seamless integration and optimal performance of critical business applications. Learning Azure not only enhances your career prospects but also significantly increases your earning potential, as certified Azure professionals are highly valued in the job market.
Embrace the power of cloud computing and take your career to new heights by mastering Microsoft Azure, and unlock a world of new possibilities and opportunities in this exciting, ever-evolving field.
