course | Microsoft Certified: Azure Data Scientist Associate
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IT-1017 | Microsoft Certified: Azure Data Scientist Associate
Course Sector : Information Technology
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 2025-09-21 | 2025-09-25 | Dubai | $4,250 | Book now |
| 5 Days | 2025-05-12 | 2025-05-16 | Barcelona | $4,950 | Book now |
| 5 Days | 2025-08-18 | 2025-08-22 | Dubai | $4,250 | Book now |
Course Introduction
Microsoft Certified: Azure Data Scientist Associate
The Microsoft Certified: Azure Data Scientist Associate course is designed to equip learners with the essential skills to effectively utilize Azure Machine Learning for data science projects. This course covers the complete lifecycle of a data science project, from data preparation to model deployment and management, enabling participants to build robust machine learning solutions on the Azure platform.
Course objective
- Understand the Azure Machine Learning environment and its components.
- Prepare and transform data for machine learning applications.
- Build, evaluate, and optimize machine learning models using Azure ML.
- Deploy machine learning models as web services and integrate them into applications.
- Manage and govern machine learning models throughout their lifecycle.
- Apply best practices for ethical AI and data science.
Course Outline | Day 01
Introduction to Azure Machine Learning
- Overview of Azure Machine Learning
- Understanding the data science lifecycle
- Setting up an Azure Machine Learning workspace
Data Preparation
- Data ingestion and exploration
- Data cleaning and transformation
- Feature engineering techniques
- Using Azure Data Factory for data integration
Course Outline | Day 02
Building Machine Learning Models
- Selecting algorithms for different scenarios
- Training machine learning models using Azure ML
- Utilizing automated machine learning (AutoML)
- Experiment tracking with Azure ML
Course Outline | Day 03
Model Evaluation and Optimization
- Evaluating model performance metrics
- Hyperparameter tuning techniques
- Cross-validation and model selection
- Handling imbalanced datasets
Model Deployment
- Deploying models as web services
- Using Azure Kubernetes Service for model deployment
- Configuring endpoints and testing deployments
- Versioning and rollback of models
Course Outline | Day 04
Consuming Deployed Models
- Integrating models with applications
- Using Azure Logic Apps and Power Apps
- Securing access to deployed models
- Monitoring and logging model performance
Course Outline | Day 05
Model Management and Governance
- Maintaining and retraining models
- Implementing model governance practices
- Managing data drift and model accuracy
- Best practices for model lifecycle management
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
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