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AWS Cloud/AI Services

Information Technology > Cloud-based management

Description

The AWS Cloud/AI Services skill equips an AI-Driven Strategy Consultant with the expertise to leverage Amazon Web Services for cloud computing and artificial intelligence solutions. This skill involves understanding AWS's global infrastructure, managing cloud resources, and implementing AI services like machine learning and data analytics. Consultants use these capabilities to design scalable, secure, and cost-effective cloud architectures that drive business innovation. They also integrate AI tools to enhance decision-making and strategic planning in consulting projects. Mastery of this skill enables consultants to guide organizations in adopting cutting-edge technologies, optimizing operations, and achieving competitive advantages in the rapidly evolving fields of cloud computing and artificial intelligence.

Expected Behaviors

✎
LEVEL 1

Fundamental Awareness

Individuals at this level have a basic understanding of AWS Cloud/AI Services, recognizing key concepts and terminology. They can navigate the AWS Management Console and comprehend the shared responsibility model, but require guidance for practical application.

🌱
LEVEL 2

Novice

Novices can perform simple tasks like setting up IAM users and launching EC2 instances. They understand basic security measures and serverless concepts, but still rely on instructions and support for more complex operations.

🌍
LEVEL 3

Intermediate

Intermediate users can design VPCs, configure auto-scaling, and deploy applications using Elastic Beanstalk. They integrate RDS with applications and utilize AI services, demonstrating a solid grasp of AWS tools and services with minimal supervision.

⭐
LEVEL 4

Advanced

Advanced practitioners architect multi-region deployments, implement advanced security features, and optimize performance with Trusted Advisor. They develop machine learning models and automate infrastructure, showcasing a high level of competence and independence.

🏆
LEVEL 5

Expert

Experts design enterprise-scale solutions, conduct security audits, and lead cloud migration strategies. They innovate with AWS AI and machine learning, driving business transformation and providing strategic insights, demonstrating mastery and leadership in the field.

Micro Skills

✎
LEVEL 1

Fundamental Awareness

Identify AWS Regions and Availability Zones
Explain the purpose of Edge Locations
Describe the benefits of AWS Global Infrastructure
Understand the concept of data residency and compliance
Log in to the AWS Management Console
Navigate the AWS Dashboard
Access different AWS services from the console
Customize the AWS Management Console interface
Define IAM roles, users, and policies
Understand IAM best practices
Create a new IAM user with specific permissions
Explain the concept of least privilege in IAM
Understand the AWS Free Tier offerings
Explain the Pay-as-you-go pricing model
Identify cost management tools in AWS
Review and interpret AWS billing and usage reports
Define the AWS Shared Responsibility Model
Differentiate between AWS and customer responsibilities
Identify security responsibilities under the model
Explain how the model applies to different AWS services
🌱
LEVEL 2

Novice

Creating a new IAM user in the AWS Management Console
Assigning permissions to IAM users using policies
Creating and managing IAM groups for user organization
Applying password policies for IAM users
Enabling multi-factor authentication (MFA) for IAM users
Selecting an appropriate Amazon Machine Image (AMI)
Configuring instance types based on workload requirements
Setting up security groups for EC2 instances
Connecting to an EC2 instance using SSH or RDP
Stopping, starting, and terminating EC2 instances
Creating a new S3 bucket in the AWS Management Console
Configuring bucket policies and access control lists (ACLs)
Uploading and managing objects within an S3 bucket
Setting up versioning for data protection
Implementing lifecycle policies for data management
Understanding AWS security best practices
Configuring AWS CloudTrail for auditing and logging
Setting up AWS Config for resource compliance monitoring
Using AWS Trusted Advisor for security recommendations
Implementing network security with security groups and NACLs
Creating a basic AWS Lambda function
Understanding event sources and triggers for Lambda
Configuring environment variables for Lambda functions
Monitoring Lambda function performance with CloudWatch
Exploring use cases for serverless architectures
Creating a simple CloudFormation stack
Understanding CloudFormation templates and syntax
Managing stack updates and changesets
Exploring CloudFormation resources and parameters
Using CloudFormation Designer for visual stack creation
🌍
LEVEL 3

Intermediate

Understanding VPC components and architecture
Creating and configuring subnets
Setting up route tables and internet gateways
Implementing network ACLs and security groups
Configuring VPC peering connections
Setting up Auto Scaling groups and policies
Configuring Elastic Load Balancers (ELB)
Monitoring and adjusting scaling activities
Integrating Auto Scaling with CloudWatch alarms
Optimizing load balancing for performance
Creating and managing Elastic Beanstalk environments
Deploying applications using different platforms
Configuring environment variables and settings
Monitoring application health and performance
Implementing version control and rollbacks
Setting up and configuring RDS instances
Connecting applications to RDS databases
Implementing RDS security and encryption
Monitoring and optimizing RDS performance
Automating backups and maintenance tasks
Setting up CloudWatch metrics and dashboards
Configuring CloudWatch alarms and notifications
Implementing CloudWatch Logs for application logging
Analyzing log data with CloudWatch Insights
Integrating CloudWatch with other AWS services
Setting up AWS Rekognition for image analysis
Implementing text analysis with AWS Comprehend
Integrating AI services with existing applications
Configuring permissions and access for AI services
Analyzing and interpreting AI service outputs
⭐
LEVEL 4

Advanced

Understanding AWS Regions and Availability Zones
Designing Cross-Region Replication for S3
Implementing Multi-AZ RDS Deployments
Configuring Route 53 for Global Traffic Management
Utilizing AWS Global Accelerator for Performance Optimization
Creating and Managing Customer Master Keys (CMKs)
Implementing Envelope Encryption for Data Protection
Integrating KMS with AWS Services like S3 and EBS
Setting Up Key Policies and Grants
Monitoring Key Usage and Auditing with CloudTrail
Analyzing Trusted Advisor Cost Optimization Recommendations
Implementing Performance Improvement Suggestions
Utilizing Trusted Advisor for Security Best Practices
Automating Trusted Advisor Checks with AWS CLI
Interpreting Service Limits and Usage Reports
Setting Up SageMaker Notebooks for Model Development
Training Models Using Built-in Algorithms
Deploying Models to SageMaker Endpoints
Monitoring and Debugging Model Performance
Utilizing SageMaker Pipelines for Workflow Automation
Writing CloudFormation Templates for Resource Provisioning
Managing Infrastructure as Code with Terraform
Implementing Change Sets and Stack Updates in CloudFormation
Using Terraform Modules for Reusability
Integrating CloudFormation with CI/CD Pipelines
Designing State Machines with AWS Step Functions
Integrating Step Functions with Lambda and Other AWS Services
Implementing Error Handling and Retry Logic
Monitoring and Debugging Executions
Optimizing Workflow Performance and Cost
🏆
LEVEL 5

Expert

Understanding the Five Pillars of the AWS Well-Architected Framework
Conducting Well-Architected Reviews for Existing Architectures
Implementing Best Practices for Operational Excellence
Ensuring Security and Compliance in Cloud Architectures
Optimizing Performance Efficiency for Large-Scale Deployments
Managing Cost Optimization Strategies in AWS
Building Reliable and Resilient Systems
Setting Up and Configuring AWS Kinesis Streams
Developing Producers and Consumers for Kinesis Data Streams
Integrating Kinesis with AWS Lambda for Real-Time Processing
Utilizing Kinesis Data Firehose for Data Delivery
Monitoring and Troubleshooting Kinesis Applications
Scaling Kinesis Applications for High Throughput
Securing Data in Transit and at Rest in Kinesis
Setting Up and Configuring AWS DeepLens Devices
Developing and Deploying Computer Vision Models on DeepLens
Training Reinforcement Learning Models with AWS DeepRacer
Participating in AWS DeepRacer League Competitions
Integrating DeepLens and DeepRacer with Other AWS Services
Optimizing Model Performance for Edge Devices
Troubleshooting and Debugging AI Models on AWS Devices
Performing Security Assessments Using AWS Security Hub
Implementing AWS Config for Continuous Compliance Monitoring
Conducting Penetration Testing in AWS Environments
Utilizing AWS CloudTrail for Audit Logging and Monitoring
Ensuring Data Protection with AWS Encryption Services
Managing Identity and Access with Advanced IAM Policies
Reporting and Mitigating Security Incidents in AWS
Assessing On-Premises Workloads for Cloud Readiness
Developing a Cloud Migration Plan and Roadmap
Executing Lift-and-Shift Migrations with AWS Migration Hub
Refactoring Applications for Cloud-Native Architectures
Managing Data Migration with AWS Database Migration Service
Ensuring Business Continuity During Migration
Post-Migration Optimization and Validation
Identifying Business Use Cases for AI and ML
Developing Custom Machine Learning Models with SageMaker
Leveraging Pre-Trained AI Services like Amazon Polly and Lex
Integrating AI Solutions into Business Processes
Measuring ROI and Impact of AI Implementations
Staying Updated with Latest AWS AI/ML Innovations
Driving Organizational Change with AI-Driven Insights

Skill Overview

  • Expert4 years experience
  • Micro-skills152
  • Roles requiring skill1

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