- 1. 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.
- 2. 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.
- 3. 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.
- 4. 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.
- 5. How is the bootcamp delivered?The bootcamp is available in two formats:
- In-person training at the DreamsPlus center in Chennai, offering direct instructor interaction.
- Online live sessions for remote learning, ensuring flexibility for learners worldwide.
- 6. Will the bootcamp help me pass the AI-102 exam?Yes, the curriculum is aligned with the AI-102: Designing and Implementing an Azure AI Solution exam syllabus. It combines theoretical knowledge and hands-on experience, preparing you effectively for the certification exam.
- 7. What skills will I acquire from this bootcamp?Upon completion, you will:
- Understand how to work with Azure’s AI services such as Computer Vision, NLP, and Machine Learning Studio.
- Gain practical skills to design and implement AI models and workflows.
- Learn how to implement responsible AI practices, ensuring fairness, security, and accountability in your AI solutions.
- 8. How much hands-on experience will I gain?The bootcamp focuses heavily on hands-on experience, with practical workshops on designing machine learning solutions, building models using Azure’s tools, and deploying them. You will work on real-world scenarios to cement your skills.
- 9. Will I receive a certificate after completing the course?Yes, you will receive a DreamsPlus Completion Certificate. The bootcamp is designed to equip you with the skills required for the Azure Machine Learning Engineer Associate Certification, which you can pursue separately.
- 10. How can I register or get more information?To register or learn more about the course:
- 📞 Call: +91 95000 56713
- 📧 Email: support@dreamsplus.in For more details, visit dreamsplus.in and get started today!
Azure Cloud
Azure Machine Learning Engineer Associate Boot Camp
Get hands-on experience with Azure Security Engineer Associate Boot Camp in Chennai and online. Prepare for Microsoft…
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Azure Machine Learning Certification Course – Learn AI on the Cloud
DreamsPlus offers a comprehensive Azure Machine Learning Engineer Associate Boot Camp in Chennai and online, tailored to provide hands-on experience and prepare you for the Microsoft certification in machine learning. This program is specifically designed to equip you with the skills needed to excel as an Azure Machine Learning Engineer Associate.
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.
FAQs for Azure Machine Learning Engineer Associate Bootcamp
What Will You Learn?
- Learn machine learning concepts for the Azure Machine Learning Engineer Associate certification
- Understand Azure services and architecture for Microsoft certification.
- Develop and implement machine learning models.
- Gain hands-on experience through workshops.
Course Curriculum
Course Benefits
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Prepare for the Azure Machine Learning Engineer Associate certification.
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Enhance machine learning skills with Microsoft certification.
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Boost career prospects in Azure machine learning.
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Stay competitive with recognized credentials
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