- Overview of Azure AI services and their applications in modern business.
- Understanding the role of an Azure AI Engineer in solution design and deployment.
- Exploring key Azure tools like Cognitive Services, Azure Machine Learning, and Bot Services.
- Introduction to the AI-102 certification exam structure and objectives.
Microsoft Certification Training Course
Microsoft Certified Azure AI Engineer Associate Certification Training Course AI-102
Design and implement AI solutions on Azure with Accumentum’s Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102), an in-depth exploration of Cognitive Services, machine learning, natural language processing, and computer vision.
Course focus: Azure Cognitive Services, machine learning model design and deployment, natural language processing, computer vision, data preparation, AI security and compliance, workflow optimization, and enterprise AI integration.
Course Overview
Build, secure, and scale AI solutions on Microsoft Azure.
The Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102) with Accumentum offers an in-depth exploration of Azure AI technologies, tailored for IT professionals, data scientists, and individuals looking to specialize in artificial intelligence within the cloud. This course emphasizes designing and implementing AI solutions on Azure, covering key areas such as building and deploying machine learning models, integrating natural language processing, implementing computer vision solutions, managing Azure Cognitive Services, optimizing AI workflows, and ensuring secure and scalable AI deployments. Through hands-on labs and real-world scenarios, participants will gain practical skills to develop AI applications, evaluate AI opportunities in the cloud, understand design principles, and assess the strategic impact of AI solutions in business contexts, preparing them for the AI-102 exam to earn the Microsoft Certified: Azure AI Engineer Associate certification.
Course Objectives
Course objectives for the Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102).
01
Design AI Solutions on Azure
Equip participants with the skills to design and implement AI solutions using Azure Cognitive Services, including natural language processing, computer vision, and machine learning model deployment.
02
Build and Secure AI Workflows
Provide hands-on experience in building, optimizing, and securing AI workflows on Azure, ensuring scalable and efficient integration with enterprise applications.
03
Apply AI to Business Requirements
Enable learners to evaluate business requirements and apply Azure AI tools to develop practical, real-world solutions that address industry-specific challenges.
04
Prepare for the AI-102 Exam
Prepare participants for the AI-102 exam by mastering key concepts, such as AI solution architecture, data preparation, and performance monitoring, to earn the Microsoft Certified: Azure AI Engineer Associate certification.
Who Should Attend
- Individuals seeking to expand their expertise by integrating AI solutions into Azure-based applications and services.
- Professionals aiming to leverage Azure’s AI tools, such as Cognitive Services and machine learning, to build scalable, real-world AI models.
- Azure practitioners looking to specialize in AI implementation and enhance their ability to design intelligent cloud solutions.
- Individuals preparing for the AI-102 exam who want hands-on experience and a deep understanding of Azure AI technologies to earn the certification.
Prerequisites
- Familiarity with core Azure concepts, such as virtual machines, storage, and networking, to effectively navigate the Azure platform.
- Proficiency in at least one programming language, such as Python or C#, to work with Azure AI tools and develop AI solutions.
- A foundational understanding of data processing, storage, and manipulation, including experience with datasets and APIs.
- Prior exposure to AI principles, such as machine learning models or natural language processing, to build on during the course.
Pathway Map
The AI-102 training course follows the Azure AI solution lifecycle.
The curriculum moves from Azure AI fundamentals and Cognitive Services through machine learning, NLP, computer vision, data preparation, security and compliance, optimization and scaling, enterprise integration, and AI-102 exam preparation.
1
Introduction to Azure AI Fundamentals
2
Working with Azure Cognitive Services
3
Designing Machine Learning Solutions
4
Natural Language Processing (NLP) on Azure
5
Computer Vision Solutions
6
Data Preparation and Processing
7
Security and Compliance in AI Solutions
8
Optimizing and Scaling AI Workflows
9
Integrating AI with Enterprise Applications
10
Preparing for the AI-102 Exam
Course Content
- Configuring pre-built APIs for vision, speech, language, and decision-making tasks.
- Implementing Cognitive Services for real-time data processing and analysis.
- Managing resource deployment and authentication for Cognitive Services in Azure.
- Hands-on labs to integrate Cognitive Services into sample applications.
- Building and training machine learning models using Azure Machine Learning.
- Selecting appropriate algorithms and datasets for specific use cases.
- Deploying machine learning models as scalable web services in Azure.
- Monitoring and evaluating model performance with Azure tools.
- Implementing text analytics for sentiment analysis, key phrase extraction, and entity recognition.
- Configuring Azure Language Understanding (LUIS) for intent-based applications.
- Developing conversational AI solutions with Azure Bot Services and NLP integration.
- Optimizing NLP models for accuracy and performance in production environments.
- Using Azure Computer Vision to analyze and interpret images and videos.
- Implementing object detection, facial recognition, and optical character recognition (OCR).
- Integrating vision APIs into applications for real-world scenarios like content moderation.
- Securing and scaling vision-based solutions in Azure.
- Identifying data requirements and sources for AI solution development.
- Using Azure Data Factory and Databricks for data ingestion and transformation.
- Cleaning and preparing datasets for machine learning and Cognitive Services.
- Ensuring data quality and compliance with Azure governance tools.
- Implementing authentication and authorization for AI resources using Azure Active Directory.
- Securing data and models with encryption and access control best practices.
- Addressing compliance requirements, such as GDPR, in AI deployments.
- Monitoring and auditing AI solutions for security vulnerabilities.
- Configuring autoscaling for AI services to handle variable workloads.
- Optimizing resource usage and cost management in Azure AI deployments.
- Using Azure Monitor and Application Insights to track performance metrics.
- Troubleshooting and resolving common performance bottlenecks in AI applications.
- Connecting Azure AI solutions with existing business systems and workflows.
- Leveraging Azure Logic Apps and Power Automate for automated AI-driven processes.
- Building end-to-end AI pipelines with integration into Microsoft 365 or third-party tools.
- Case studies on successful enterprise AI implementations.
- Reviewing key concepts and skills tested in the Microsoft AI-102 certification exam.
- Practicing with mock scenarios and sample questions aligned with exam objectives.
- Strategies for designing and troubleshooting AI solutions under exam conditions.
- Final hands-on project to demonstrate mastery of Azure AI engineering principles.
Course Features
Course features of the Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102).
Interactive Learning
Participate in training sessions, discussions, and hands-on labs with experienced instructors.
Practical Scenarios
Engage in real-world exercises and case studies to apply your knowledge.
Comprehensive Study Materials
Access extensive resources, including e-books, video lectures, and practice exams.
Certification Preparation
Receive guidance and tips to successfully pass the Microsoft Certified Azure AI Engineer Associate (AI-102) certification exam.
Certification Exam
Prepare for the Microsoft Certified: Azure AI Engineer Associate (AI-102) exam.
AI-102 Exam Readiness
Accumentum’s AI-102 Training Course prepares learners to design, implement, and manage machine learning models, natural language processing, and computer vision solutions on Azure.
Upon completing the Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102) with Accumentum, you will be fully prepared to pass the AI-102 exam. This certification validates your expertise in Azure AI technologies, including the design, implementation, and management of machine learning models, natural language processing, and computer vision solutions. It demonstrates your proficiency in optimizing AI workflows, ensuring security and scalability, and utilizing Azure’s AI tools to deliver intelligent cloud-based applications. Achieving the Microsoft Certified: Azure AI Engineer Associate certification will enhance your career opportunities, positioning you for roles that require advanced AI skills and strategic implementation of Azure AI solutions for business innovation and success.
Frequently Asked Questions
Understand how Accumentum’s Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102) supports certification readiness, course delivery, and career advancement.
The certification validates your expertise in Azure AI technologies, including the design, implementation, and management of machine learning models, natural language processing, and computer vision solutions. It demonstrates your proficiency in optimizing AI workflows, ensuring security and scalability, and utilizing Azure’s AI tools to deliver intelligent cloud-based applications.
The course suits individuals seeking to expand their expertise by integrating AI solutions into Azure-based applications and services, professionals aiming to leverage Azure’s AI tools to build scalable real-world AI models, Azure practitioners specializing in AI implementation, and individuals preparing for the AI-102 exam.
Familiarity with core Azure concepts such as virtual machines, storage, and networking is expected, along with proficiency in at least one programming language such as Python or C#, a foundational understanding of data processing, storage, and manipulation, and prior exposure to AI principles such as machine learning models or natural language processing.
The curriculum covers Introduction to Azure AI Fundamentals, Working with Azure Cognitive Services, Designing Machine Learning Solutions, Natural Language Processing (NLP) on Azure, Computer Vision Solutions, Data Preparation and Processing, Security and Compliance in AI Solutions, Optimizing and Scaling AI Workflows, Integrating AI with Enterprise Applications, and Preparing for the AI-102 Exam.
Yes. A dedicated module covers configuring pre-built APIs for vision, speech, language, and decision-making tasks, implementing Cognitive Services for real-time data processing and analysis, managing resource deployment and authentication, and hands-on labs to integrate Cognitive Services into sample applications.
Yes. The Designing Machine Learning Solutions module covers building and training models using Azure Machine Learning, selecting appropriate algorithms and datasets, deploying models as scalable web services in Azure, and monitoring and evaluating model performance with Azure tools.
The Security and Compliance in AI Solutions module covers implementing authentication and authorization using Azure Active Directory, securing data and models with encryption and access control best practices, addressing compliance requirements such as GDPR, and monitoring and auditing AI solutions for security vulnerabilities.
The course features interactive learning, where you participate in training sessions, discussions, and hands-on labs with experienced instructors, plus practical scenarios that let you engage in real-world exercises and case studies to apply your knowledge.
You receive comprehensive study materials with access to extensive resources, including e-books, video lectures, and practice exams, along with certification preparation guidance and tips to successfully pass the AI-102 certification exam.
Enroll in the Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102) with Accumentum to elevate your AI expertise in the cloud and earn a globally recognized certification. For complete details and to secure your spot, visit Accumentum's registration page linked below.
Enrollment
Enroll in the Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102).
Enroll in the Microsoft Certified: Azure AI Engineer Associate Certification Training Course (AI-102) with Accumentum to elevate your AI expertise in the cloud and earn a globally recognized certification. This course is your gateway to becoming a Microsoft Certified: Azure AI Engineer Associate. For complete details and to secure your spot, visit Accumentum's registration page linked below.
Elevate your AI expertise with AI-102 training.
Prepare for the AI-102 exam, design and deploy machine learning, NLP, and computer vision solutions, and integrate secure, scalable AI workflows across the enterprise.