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• Describe Artificial Intelligence workloads and considerations
• Describe fundamental principles of machine learning on Azure
• Describe features of computer vision workloads on Azure
• Describe features of Natural Language Processing (NLP) workloads on Azure
• Describe features of conversational AI workloads on Azure

• State different kinds of solutions AI can make possible and considerations for responsible AI practices.
• Describe the core concepts of machine learning.
• Identify different types of machine learning.
• Describe considerations for training and evaluating machine learning models.
• Describe core concepts of deep learning.
• Use automated machine learning in Azure Machine Learning service.

• Explain the core concepts and components of cloud infrastructure, including virtual machines, networks, storage, and identity services.
• Optimize compute resources for performance, cost, and scalability.
• Implement and troubleshoot network connectivity between cloud resources.
• Understand the basic concepts of cloud databases, including Cloud SQL and Cloud Firestore.
• Apply security best practices for data protection, encryption, and compliance in the cloud environment.

• Explain the value of AWS Cloud.
• Understand and explain the AWS shared responsibility model.
• Understand AWS Cloud security best practices.
• Understand AWS Cloud costs, economics, and billing practices.
• Describe and position the core AWS services, including compute, network, databases, and storage.
• Identify AWS services for common use cases.

• Identify the key features of the core AWS technologies used to build serverless applications, like S3, DynamoDB, Elastic Beanstalk, Lambda, and API Gateway.
• Build, deploy, and troubleshoot serverless applications in AWS.
• Use AWS CLI, AWS service APIs, and SDKs to interact with AWS.
• Create a CI/CD pipeline to deploy applications on AWS.
• Implement AWS security best practices using IAM, KMS, and MFA.
• Configure AWS services for optimal performance.

• Design and implement distributed systems on AWS.
• Design cost and performance optimized solutions, demonstrating a strong understanding of the AWS Well-Architected Framework.
• Make informed decisions about when and how to apply key AWS Services for compute, storage, database, networking, monitoring, and security.
• Design architectural solutions to address common business challenges.
• Create and operate a data lake in a secure and scalable way, ingest and organize data into the data lake, and optimize performance and costs.
• Prepare for the certification exam, identify your strengths and gaps for each domain area, and build strategies for identifying incorrect responses.
• Deploy, manage, and operate workloads on AWS as well as implement security controls and compliance requirements.
• Use the AWS Management Console and the AWS Command Line Interface (CLI).
• Identify which AWS services meet a given technical requirement and define technical requirements for an AWS-based application.

At the end of this course, participants should be able to:

• Understand Azure Kubernetes Service (AKS) and its core features.
• Deploy and configure AKS clusters according to best practices.
• Manage and scale applications running on AKS.
• Implement AKS networking and integrate with other Azure services.
• Set up monitoring, logging, and maintain AKS security.
• Automate AKS deployments using continuous integration and continuous deployment (CI/CD) pipelines.
• Troubleshoot common issues in AKS environments.
• Explore advanced AKS topics such as multi-region deployment and service mesh integration.

At the end of this course, participants should be able to:

• Configure Virtual Networks and subnets, including IP addressing
• Configure an Azure Virtual Network peering connection and address transit and connectivity concerns.
• Control Azure Virtual Network traffic by implementing custom routes.
• Configure Azure DNS to host your domain.
• Implement network security groups and ensure network security group rules are correctly applied
• Explain how Azure Firewall and Azure Firewall Manager work together to protect Azure virtual networks.

At the end of the course, participants will be able to:

• Create an Azure Storage account with the correct options for their business needs.
• Configure Azure Blob Storage, including tiers and object replication.
• Configure common Azure Storage security features like storage access signatures.
• Ensure data is stored, transferred, and accessed in a secure way using Azure storage and file security features.
• Understand how network security groups and service endpoints help you secure your virtual machines and Azure services from unauthorized network access.

At the end of the course, participants will be able to:

• Understand Azure Monitor and its components.
• Configure data sources for Azure Monitor.
• Implement data collection for Azure resources and non-Azure environments.
• Set up alerts and actions with Azure Monitor.
• Create and customize dashboards for data visualization.
• Utilize Log Analytics for querying and analyzing monitoring data.
• Implement Application Insights for application performance monitoring.
• Optimize and scale Azure monitoring solutions.