Microsoft Certified: Azure Data Scientist Associate

Course Code: IT 1812

11 Course Visits

Course Sector:

Information Technology

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Course Dates and Locations

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No.

Date

Days

Location

Fees

Enrollment

21 - 26 Sep 2025

5 Days

Dubai, UAE

$4,900

Introduction

Training course introducion / brief

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.

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.

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.

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

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

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

Consuming Deployed Models

Integrating models with applications
Using Azure Logic Apps and Power Apps
Securing access to deployed models
Monitoring and logging model performance

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 certificate of completion

BOOST's Professional Attendance Certificate “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.

ENDORSED EDUCATION PROVIDER

Flexible deadlines

Customized dates accordance to your schedule

Shareable Certificate

Earn certificate upon completion

COURSE METHODOLOGY

Our Training programs are implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).

At The end of the training program, Participants are involved in practical workshop to show their skills in applying what they were trained for. A detailed report is submitted to each participant and the training department in the organization on the results of the participant's performance and the return on training. Our programs focus on exercises, case studies, and individual and group presentations.

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TRAINING COURSE: Microsoft Certified: Azure Data Scientist Associate