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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.
CT CASP-005
At the end of this A1-050 training, participants should be able to:

  • 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.
MS AI-050
At the end of this AI-102 training, participants should be able to:

  • 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.
MS AI-102

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.
MS AI-3003
At the end of this AI-900 training, participants should be able to:

  • 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.
MS AI-900
4 days (32 hours)
At the end of this training, you will be able to:

  • 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.
EV8 TECH-001
10 days (300 hours)
By the end of the training, participants should be able to:

  • 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.
Ev8 ACE-001
At the end of the training, participants should be able to:

  • 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.
AWS CLF-C01
At the end of this training, participants should be able to:

  • 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.
AWS DVA-C02
At the end of this training, participants should be able to:

  • 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.
AWS SAA-C03
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