As a candidate for this certification, you should have subject matter expertise in applying data science and machine learning to implement and run machine learning workloads on Azure.
Your responsibilities for this role include:
- Designing and creating a suitable working environment for data science workloads.
- Exploring data.
- Training machine learning models.
- Implementing pipelines.
- Running jobs to prepare for production.
- Managing, deploying, and monitoring scalable machine learning solutions.
As a candidate for this certification, you should have knowledge and experience in data science by using:
- Azure Machine Learning
- MLflow
- Design and prepare a machine learning solution
- Explore data and train models
- Prepare a model for deployment
- Deploy and retrain a model
- Data Scientists
- Data Engineers
- Machine Learning Engineers
- AI Developers
- IT Professionals
- Data Analysts
- Business Intelligence Professionals
- Researchers and Academia
Required
- Creating cloud resources in Microsoft Azure.
- Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
- Working with containers
Recommended
- Lesson: Design a data ingestion strategy for machine learning projects
- Lesson: Design a machine learning model training solution
- Lesson: Design a model deployment solution
- Lesson: Explore Azure Machine Learning workspace resources and assets
- Lesson: Explore developer tools for workspace interaction
- Exercise – Explore the Azure Machine Learning workspace
- Exercise – Explore developer tools for workspace interaction
- Lesson: Make data available in Azure Machine Learning
- Exercise – Make data available in Azure Machine Learning
- Lesson: Work with compute targets in Azure Machine Learning
- Lesson: Work with environments in Azure Machine Learning
- Exercise – Work with compute resources in Azure Machine Learning
- Exercise – Work with environments in Azure Machine Learning
- Lesson: Explore Automate Machine Learning
- Lesson: Find the best classification model with Automated Machine Learning
- Exercise – Find the best classification model with Automated Machine Learning
- Lesson: Track model training in notebooks with MLflow
- Exercise – Track model training in notebooks with MLflow
- Lesson: Run a training script as a command job in Azure Machine Learning
- Lesson: Track model training with MLflow in jobs
- Lesson: Perform hyperparameter tuning with Azure Machine Learning
- Exercise – Run a training script as a command job in Azure Machine Learning
- Exercise – Use MLflow to track training jobs
- Exercise – Perform hyperparameter tuning with a sweep job
- Lesson: Run pipelines in Azure Machine Learning
- Exercise – Run pipelines in Azure Machine Learning
- Lesson: Register an MLflow model in Azure Machine Learning
- Lesson: Manage and compare models in Azure Machine Learning
- Exercise – Log and register models with MLflow
- Exercise – Create and explore the Responsible AI dashboard
- Lesson: Deploy a model to a managed online endpoint
- Lesson: Deploy a model to a batch endpoint
- Exercise – Deploy a model to an online endpoint
- Exercise – Deploy a model to a batch endpoint
Azure Data Scientists work with data stored in Azure data storage solutions, which they access from Azure Machine Learning. They work with notebooks and scripts to train machine learning models and use Azure Machine Learning managed compute for their workloads. Azure Data Scientists should primarily focus on being proficient at using the Python SDK (v2) to interact with the Azure Machine Learning workspace, and MLflow to track and manage models. However, they should also be familiar with the Studio and Azure CLI tools
This course is for Azure Data Scientists. Azure Data Scientists are expected to perform data science tasks on Azure. The course doesn’t teach data science but expects the audience to already be familiar with basic data science and machine learning concepts.
The Azure Data Science Certification Training course teaches participants how to operate machine learning solutions at cloud scale using Azure Machine Learning. The course covers topics such as data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.
The course is available as both in-person and online training.
. If you are completely new to data science and machine learning, it is recommended that you complete Microsoft Azure AI Fundamentals Training (AI-900) before taking this course.
In the course, you will learn how to use Azure services to develop machine learning solutions, deploy machine learning models, automate machine learning with Azure Machine Learning service, and manage and monitor machine learning models with the Azure Machine Learning service.
Yes, this course can help you prepare for the Microsoft role-based certification exam DP-100: Designing and Implementing a Data Science Solution on Azure.
Attend this course and get prepped to pass Exam DP-100 to achieve Azure Data Scientist Associate certification.
Yes, the course can be brought to your organization and delivered when, where, and how you want it. The content can also be tailored to meet the specific needs of your organization.
Please reach out to info@industechservices.com after your course to obtain your exam voucher.
