Azure cloud

Azure Machine Learning Engineer Associate Boot Camp

DreamsPlus presents an extensive Azure Machine Learning Engineer Associate Boot Camp in Singapore and

Azure Machine Learning Engineer Associate Boot Camp

DreamsPlus presents an extensive Azure Machine Learning Engineer Associate Boot Camp in Singapore and through online platforms, delivering practical, hands-on training to help you achieve the Microsoft Azure Machine Learning certification. Tailored for professionals in Singapore, this program equips you with the advanced skills and knowledge required to thrive as an Azure Machine Learning Engineer Associate in today’s competitive tech industry.

Syllabus 

  • Describe Artificial Intelligence workloads and considerations (20–25%)
  • Describe fundamental principles of machine learning on Azure (25–30%)
  • Describe features of computer vision workloads on Azure (15–20%)
  • Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)

Describe Artificial Intelligence workloads and considerations (20–25%)

Identify features of common AI workloads

  •  Define characteristics of workloads for anomaly detection.
  • Determine workloads in computer vision.
  • Determine the workloads for natural language processing
  • Determine the workloads for knowledge mining

Identify guiding principles for responsible AI

  •  Explain how an AI solution should take fairness into account.
  •  Explain how an AI system should take safety and dependability into account.
  •  Describe how an AI solution takes security and privacy into account
  •  Explain how an AI solution should take inclusivity into account.
  •  Discuss the factors that should be transparent in an AI solution.
  •  Explain how an AI solution should take accountability into account.

 Describe fundamental principles of machine learning on Azure (25–30%)

Identify common machine learning types

  •  Determine machine learning scenarios for regression.
  •  Define machine learning scenarios for classification.
  •  Determine which machine learning scenarios to cluster.

Describe core machine learning concepts

  • Recognize characteristics and annotations in a dataset for machine learning
  • Explain how machine learning uses training and validation datasets.
  • Explain the features of Azure Machine Learning Studio’s visual tools.
  •  Machine learning that is automated
  •  Azure Machine Learning Designer

Describe features of computer vision workloads on Azure (15–20%)

Identify common types of computer vision solution

  • Define characteristics of image classification algorithms.
  •  List the characteristics of object detecting programs.
  • List the characteristics of optical character recognition programs.
  •  List the characteristics of facial analysis and detecting software.

Identify Azure tools and services for computer vision tasks

  • Determine the Computer Vision service’s capabilities
  • List the features that the Custom Vision service offers.
  • Determine what features the Face service offers.
  • Figure out the form recognition service’s capabilities.

Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)

Identify features of common NLP workload scenarios

  • Define characteristics and applications of key phrase extraction.
  • Determine entity recognition features and applications.
  • Define sentiment analysis’s characteristics and applications.
  •  Determine the features and applications of language modeling; • Determine the features and applications of voice recognition and synthesis;
  •  Describe the functions and attributes of translation.

Identify Azure tools and services for NLP workloads

  • Determine the language service’s capabilities.
  • Establish the speech service’s capabilities.
  •  Determine the translator service’s capabilities.

Identify considerations for conversational AI solutions on Azure

  • List the functions and attributes of bots.
  • List the features of the Azure Bot service and Power Virtual Agents.

Course Curriculum

Prepare for the Azure Machine Learning Engineer Associate certification.

Enhance machine learning skills with Microsoft certification.

Boost career prospects in Azure machine learning.Boost career prospects in Azure machine learning.

Stay competitive with recognized credentials

 
 
DreamsPlus Azure Machine Learning Engineer Associate Training Package

FAQs for Azure Machine Learning Engineer Associate Bootcamp

What is the Azure Machine Learning Engineer Associate Bootcamp?

The Azure Machine Learning Engineer Associate Bootcamp by DreamsPlus is a comprehensive training program aimed at preparing you for the Microsoft Azure Machine Learning Engineer Associate Certification (Exam: AI-102). It focuses on machine learning workflows, tools, and technologies within the Azure ecosystem.

Who should attend this bootcamp?

This bootcamp is ideal for:

  • Aspiring Machine Learning Engineers looking to specialize in Azure services.
  • Data scientists and AI professionals who want to build and deploy machine learning models on Azure.
  • Professionals pursuing the AI-102 certification to enhance their career opportunities.
What topics are covered in this course?

Key topics include:

  • Principles of machine learning on Azure.
  • AI workload management including anomaly detection, computer vision, and natural language processing (NLP).
  • Responsible AI practices.
  • Tools and services for implementing machine learning models in Azure.
What prerequisites do I need before joining the bootcamp?

A basic understanding of:

  • Machine Learning concepts and algorithms.
  • Experience with data analysis and Python programming is helpful but not mandatory.
  • Familiarity with Azure fundamentals is a plus, but the bootcamp will cover essential Azure-specific training.
How can I register or get more information?

To register or learn more about the course:

  • 📞 Call: +65 8205 0700
  • 📧 Email: support@dreamsplus.sg
    For more details, visit dreamsplus.sg and start your journey towards Azure security certification today!
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