course | Microsoft Certified: Azure Data Scientist Associate
Microsoft Certified: Azure Data Scientist Associate course teaches data modeling, machine learning, Azure AI solutions, predictive analytics, and data strategy.
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 | 21/09/2026 | 25/09/2026 | Dubai | $4,250 | Book now |
| 5 Days | 04/04/2027 | 08/04/2027 | Riyadh | $4,250 | Book now |
| 5 Days | 24/05/2027 | 28/05/2027 | Barcelona | $4,950 | Book now |
| 5 Days | 30/08/2027 | 03/09/2027 | Dubai | $4,250 | Book now |
Course Introduction
The Microsoft Certified: Azure Data Scientist Associate course is designed for data professionals who want to enhance their skills in building, training, and deploying machine learning models on Microsoft Azure. Participants will learn how to analyze data, develop predictive models, and leverage cloud-based AI solutions to solve real-world business problems.
This course covers key topics such as data exploration, feature engineering, model training, evaluation, and deployment using Azure Machine Learning services. Learners will gain hands-on experience with data preprocessing, supervised and unsupervised learning, automated machine learning (AutoML), and model monitoring to ensure high-quality, accurate predictions.
Participants will also understand data strategy, Azure AI integration, and best practices for data science workflows, enabling them to design scalable and efficient machine learning pipelines. The program emphasizes practical applications, empowering data scientists to make data-driven decisions that support organizational goals.
This training is ideal for data scientists, machine learning engineers, AI developers, and IT professionals who want to certify their expertise with the Microsoft Azure platform. By completing the course, participants will be prepared to earn the Microsoft Certified: Azure Data Scientist Associate certification and apply their knowledge to advanced data science projects in the cloud
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 audience
- Data scientists and machine learning practitioners seeking to enhance their skills in Azure.
- IT professionals looking to specialize in data science and machine learning on the Azure platform.
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.
Since 2001, we’ve been at the forefront of professional training in the Middle East — shaping the future of learning and development one success story at a time. With a vision rooted in innovation and excellence, we help individuals, teams, and organizations reach their highest potential through integrated, future-ready training solutions. Our comprehensive programs combine global best practices with local insights, empowering people to grow, lead, and make a lasting impact in their industries.
🔗 Quick Links
Sister Companies to Boost Consulting and Training
most trending
And Recommended Training Courses
We believe in progress for everyone.
We helped more than 10,000 clients over 20 countries on 4 continents in boosting their knowledge, skills, and careers.
Boost Training And Consulting All Copyrights Reserved 2026