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

• Analyze security requirements in hybrid networks to work toward an enterprise-wide, zero-trust security architecture with advanced secure cloud and virtualization solutions.
• Address advanced threat management, vulnerability management, risk mitigation, incident response tactics and digital forensic analysis.
• Prove an organization's overall cybersecurity resiliency metric and compliance to regulations.
• Configure for endpoint security controls, enterprise mobility, cloud/hybrid environments and enterprise-wide PKI.

• Design and implement generative artificial intelligence models using the Azure platform.
• Build, evaluate, and optimize AI models.
• Manage and Monitor AI workflows.
• Integrate AI solutions into business processes.
• Develop proficiency in leveraging Azure's pre-built AI capabilities.

• Design, implement, and monitor AI solutions in Microsoft Azure.
• Use cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions.
• Implement computer vision, natural language processing, and conversational AI.
• Manage and optimize AI solutions.

At the end of the AI-3003 training, participants should be able to:

• Deploy a language resource and use prebuilt models.
• Create a custom text classification solution.
• Create a custom named entity recognition (NER) solution.

• Describe cloud concepts.
• Describe core Azure services.
• Describe security, privacy, compliance, and trust.
• Describe Azure pricing, Service Level Agreements, and Lifecycles.
• Leverage the lab environment during the instructional portion of the class.

• 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.