DP-100: Designing and Implementing a Data Science Solution on Azure (DP-100T01-A) (EN)
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What is DP-100: Designing and Implementing a Data Science Solution on Azure (DP-100T01-A)
This training is designed to help you understand how to operate machine learning solutions at cloud scale using Azure Machine Learning. It will enable 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.
Undergoing training in ‘DP-100: Designing and Implementing a Data Science Solution on Azure’ equips you with practical insights and industry best practices. Our trainers, with their rich expertise, bring a tangible aspect to the theoretical concepts, offering invaluable real-world insights that can significantly enhance your data science journey. This blend of theory and practice can be a game-changer in your learning experience.
Who should attend DP-100: Designing and Implementing a Data Science Solution on Azure (DP-100T01-A)
- Data Scientists: This training is ideal for data scientists looking to expand their knowledge on Azure Machine Learning.
- AI Engineers: AI engineers can benefit from learning how to implement machine learning solutions at scale.
- Machine Learning Practitioners: Those already practicing machine learning can deepen their understanding of data ingestion and preparation.
- Python Programmers: Python programmers interested in machine learning can learn how to leverage their existing skills in a new context.
- Cloud Solution Architects: Architects can learn how to design and implement a data science solution on Azure.
Prerequisites
Basic knowledge of Python programming and machine learning concepts is recommended.
Objectives
At the end of the training you will be able to:
- Provision an Azure Machine Learning workspace
- Use tools and code to work with Azure Machine Learning
- Use designer to train a machine learning model
- Deploy a designer pipeline as a service
- Run code-based experiments in an Azure Machine Learning workspace
- Train and register machine learning models
- Create and consume Datastores and Datasets
- Create and use environments and compute targets
- Create pipelines to automate machine learning workflows
- Publish and run pipeline services
- Publish a model as a real-time inference service
- Publish a model as a batch inference service
- Optimize hyperparameters for model training
- Use automated machine learning to find the optimal model for your data
- Generate model explanations with automated machine learning
- Use explainers to interpret machine learning models
- Use application insights to monitor a published model
- Monitor data drift
Exam information
Exam Information:
- Exam duration (minutes): 180 mins
- Exam style: Multiple Choice
- Open Book: No
Exam guarantee:
We have full confidence in the quality of our training. Therefore, if you take this training in our open schedule, we offer an exam guarantee. This means that you can retake the training for free, and you’ll receive a complimentary exam voucher if you don’t pass the exam on your first attempt.
The following conditions apply:
- You attended the entire training.
- You took the first exam within 2 months after the training.
- There is a maximum of 1 year between your initial training and the free training.
e-CF competences with this course
- A.5. Architecture Design
- B.1. Application Development
- B.6. ICT System Engineering
- C.5. Systems Management
Classroom, online, blended and in-company
At Capgemini Academy you learn in the way that suits you. Do you prefer classroom training, online or a combination of the two (blended)? You can follow most training courses in-company: within your own organization. We use a variety of tools to make learning even more fun and effective. Consider videos, games, quizzes, webinars and case studies, for example. And you can always contact your trainer with any questions.
In-company training courses
With an in-company training you have several advantages:
- You choose the location.
- You train with your colleagues, ensuring it aligns with your practice.
- The trainer tailors explanations, examples and assignments to your organization.
- In consultation, exercises can be adapted to organization-specific questions.
Request more information or a quote.
