A tanfolyamról
Organizations around the world routinely analyze different forms of data to enhance productivity and scale up at an exponential rate. That’s why there is an immense demand for individuals who can design and implement data solutions. This is where professionals well-versed with Data Science Solutions come into the picture.
Designing and implementing Data Science Solutions requires specialized skills and technological knowledge. The Microsoft DP-100 certification validates your expertise in the Data Science on Azure domain. It also boosts your CV. However, clearing the DP-100 exam requires a mix of practical knowledge, technical skills, fundamental concepts, and a lot more.
In this course, you learn core data, Azure, Python, and Machine Learning solutions that help you to clear the Data Engineering on Microsoft Azure course and get Microsoft Certified.
Who Should Attend the Course
- IT Professionals
- Cloud Solutions Architects
- Experienced Azure Administrators
- Azure Developers
- DevOps Professionals
- Python Experts
What You Will Learn
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Data Preparation
Leverage your Python and Machine Learning skills to manage data preparation and ingestion. -
Train Data Models
Create advanced data models by implementing Azure Machine Learning Designer. -
Data Interpretation
Learn how to use advanced framework and tools to implement data and provide data-driven results. -
Data Storage
Implement Azure storage accounts and Data warehouse to securely store different forms of data. -
Data Analysis
Use cutting-edge storage technologies to build an analytical solution for Data Analysis. -
ML Workloads on Azure
Gain the expertise in aplying data science and machine learning to run ML workloads on Azure.
During this 3-day course, a variety of topics will be covered in the context of an Azure environment. You will gain skills to:
- Create an efficient working environment for data science workloads on Azure
- Train predictive models through experiments
- Deploy, manage, and optimize ML models, and more.
To get more details about the exam and certification you can refer to the respective Microsoft page.
We provide the course in English.
Tematika
Curriculum
1. Introduction
- Azure Overview
- Fundamental Azure Concepts
- Introduction to Azure Portal
2. Manage Azure Resources for Machine Learning
- Create Azure Machine Learning Workspace
- Manage Data in Azure Machine Learning Workspace
- Manage Compute for Experiment in Azure Machine Learning Workspace
- Implement Security and Access Control in Azure
- Setup Azure Database Workspace
3. Run Experiments and Train Models
- Create Models using Azure Machine Learning Designer
- Run Model Training Scripts
- Generate Metrics from Experiments
- Create Optimal Models with Automated Machine Learning
4. Deploy and Operationalization of Machine Learning Solutions
- Select Compute for Model Deployment
- Deploy Model as a Service
- Manage Models in Azure Machine Learning
- Create Azure Machine Learning Pipeline for Batch Interfering
- Publish Azure Machine Learning Designer Pipeline as a Web Service
- Implement Pipelines by using the Azure Machine Learning SDK
- Apply ML Ops Practices
5. Implement Responsible ML
- Use Model Explainers for Data Interpretation
- Fairness Considerations for Models
- Privacy Consideration for Data
Kinek ajánljuk
Előfeltételek
Prerequisites
- Knowledge of Python and Machine Learning frameworks
- Prior experience with the Azure portal