AWS Training Syllabus
AWS Training Syllabus
Comprehensive Cloud Learning Journey
Module 1: AWS Foundation & Multi-Account Strategy
Multi-Account Strategy & Governance 2 hours
What You Will Learn:
- Design and implement a multi-account AWS environment
- Structure Organizational Units (OUs) for security and compliance
- Implement Service Control Policies (SCPs) to enforce governance
- Understand consolidated billing for cost management
Tools: AWS Organizations, Control Tower, AWS Console
Security & Compliance Fundamentals 3 hours
What You Will Learn:
- Implement IAM best practices and permission boundaries
- Configure AWS Security Hub for centralized security visibility
- Set up AWS Config for resource compliance monitoring
- Use CloudTrail for audit logging and GuardDuty for threat detection
Tools: Security Hub, IAM Analyzer, Config Rules
Module 2: AWS Well-Architected Framework
Well-Architected Framework Review 2.5 hours
What You Will Learn:
- Understand the six pillars of the Well-Architected Framework
- Conduct Well-Architected reviews for your workloads
- Identify and remediate architectural risks
- Use Trusted Advisor for automated best practice checks
Tools: Well-Architected Tool, Trusted Advisor
Module 3: Networking & Infrastructure
Advanced Networking 3 hours
What You Will Learn:
- Design VPC architectures for security and scalability
- Implement Transit Gateway for network connectivity
- Configure hybrid connectivity using Direct Connect and VPN
- Optimize global application performance with Route 53
Tools: VPC, Transit Gateway, Direct Connect, Route 53
Storage Solutions 2.5 hours
What You Will Learn:
- Select appropriate storage services for different use cases
- Implement data lifecycle policies for cost optimization
- Configure backup and disaster recovery strategies
- Set up cross-region replication for business continuity
Tools: S3, Glacier, EBS, EFS, FSx
Module 4: Compute & Application Services
Compute Services 3 hours
What You Will Learn:
- Deploy and manage EC2 instances with Auto Scaling
- Implement load balancing for high availability
- Containerize applications using ECS and EKS
- Build serverless applications with Lambda and Step Functions
Tools: EC2, Auto Scaling, ELB, ECS, EKS, Lambda
Management & Automation 2.5 hours
What You Will Learn:
- Implement Infrastructure as Code with CloudFormation
- Monitor resources and set up alerts with CloudWatch
- Automate operational tasks with Systems Manager
- Build event-driven architectures with EventBridge
Tools: CloudFormation, CloudWatch, Systems Manager, EventBridge
Module 5: Hands-On Labs
Practical Implementation 4 hours
What You Will Learn:
- Set up a complete AWS Organizations structure
- Deploy a landing zone with Control Tower
- Configure security monitoring with Security Hub
- Perform a Well-Architected Framework review
- Automate infrastructure with CloudFormation
- Implement multi-region architecture for resilience
Hands-on: AWS Console, CloudFormation, Control Tower
Module 6: FinOps - Cloud Financial Management
FinOps Fundamentals 2 hours
What You Will Learn:
- Understand core FinOps principles and practices
- Identify key roles in cloud financial management
- Establish cross-team collaboration for cost optimization
- Implement the FinOps lifecycle: Inform, Optimize, Operate
Cost Visibility & Allocation 2.5 hours
What You Will Learn:
- Analyze cloud billing and usage data
- Implement effective tagging strategies
- Set up cost allocation and chargeback/showback mechanisms
- Build dashboards for cost visibility
Tools: AWS Cost Explorer, Billing Reports
Cost Optimization Strategies 2.5 hours
What You Will Learn:
- Leverage commitment-based discounts (RIs, Savings Plans)
- Implement rightsizing and scheduling for cost efficiency
- Utilize Spot Instances with automation
- Apply various cost optimization strategies across services
Governance & Maturity 2 hours
What You Will Learn:
- Establish cloud budgeting and forecasting processes
- Define KPIs and metrics for cloud financial management
- Implement governance and policy enforcement
- Assess and improve FinOps maturity
Module 7: FinOps Tools & Practical Exercises
FinOps Tools Overview 1.5 hours
What You Will Learn:
- Evaluate popular FinOps tools (CloudHealth, Cloudability, etc.)
- Understand integration options with cloud platforms
- Establish criteria for tool selection
FinOps Hands-On Labs 3 hours
What You Will Learn:
- Use AWS Cost Explorer and Billing Reports
- Build a basic cost dashboard
- Analyze Reserved Instances vs On-Demand pricing
- Compare Spot instance costs
- Create cloud budgets and define governance policies
Tools: AWS Cost Explorer, Budgets
Module 8: AWS CLI & SDKs
AWS CLI Fundamentals 2 hours
What You Will Learn:
- Install and configure AWS CLI
- Execute commands for EC2, S3, IAM, and CloudWatch
- Automate tasks using CLI scripts
- Use AWS SDKs with Python/Boto3
Tools: AWS CLI, Python/Boto3
Module 9: Containerization with Kubernetes
Kubernetes Essentials 2.5 hours
What You Will Learn:
- Understand Kubernetes core concepts and architecture
- Deploy and manage Pods, Services, and Deployments
- Configure different service types (LoadBalancer vs ClusterIP)
- Manage containerized applications on AWS
Module 10: Infrastructure as Code
AWS CloudFormation 3 hours
What You Will Learn:
- Write CloudFormation templates in YAML/JSON
- Create, update, and manage CloudFormation stacks
- Implement nested stacks and parameters
- Manage infrastructure changes safely
Tools: CloudFormation
AWS CDK (Cloud Development Kit) 3 hours
What You Will Learn:
- Set up and configure AWS CDK
- Define infrastructure using TypeScript/Python
- Use CDK constructs for common patterns
- Execute synth, deploy, and diff commands
Tools: AWS CDK, TypeScript/Python
Module 11: CI/CD on AWS
CodePipeline & CodeBuild 3 hours
What You Will Learn:
- Design and implement CI/CD pipelines with CodePipeline
- Integrate with source repositories (GitHub/CodeCommit)
- Configure build processes with CodeBuild
- Implement manual approvals and rollback strategies
Tools: CodePipeline, CodeBuild
CodeDeploy & Advanced CI/CD 2.5 hours
What You Will Learn:
- Implement deployment strategies (Blue/Green, Canary)
- Configure deployment hooks and lifecycle events
- Monitor and troubleshoot deployments
- Build comprehensive CI/CD workflows
Tools: CodeDeploy
Module 12: Operations & Monitoring
Monitoring & Automation 2.5 hours
What You Will Learn:
- Set up CloudWatch metrics and alarms
- Build event-driven automations with EventBridge
- Create serverless automation with Lambda
- Manage resources at scale with Systems Manager
Tools: CloudWatch, EventBridge, Lambda, Systems Manager
Module 13: Terraform for AWS
Terraform Fundamentals 3 hours
What You Will Learn:
- Install and configure Terraform CLI
- Understand Terraform providers and plugin architecture
- Write basic Terraform configurations
- Execute Terraform commands: init, plan, apply, destroy
Tools: Terraform CLI
Advanced Terraform 3 hours
What You Will Learn:
- Manage Terraform state effectively
- Create and use Terraform modules
- Work with inputs, outputs, and variable scopes
- Validate and format Terraform code
Tools: Terraform
Terraform in CI/CD 2.5 hours
What You Will Learn:
- Integrate Terraform into CI/CD pipelines
- Configure Jenkins pipelines for Terraform
- Set up remote backends for state management
- Use workspaces for environment management
- Explore Terraform Cloud and Enterprise features
Tools: Terraform, Jenkins
Module 14: Hands-On Infrastructure Labs
Comprehensive Infrastructure Labs 5 hours
What You Will Learn:
- Deploy CloudFormation stacks with parameters and outputs
- Define infrastructure using AWS CDK in Python/TypeScript
- Set up complete CI/CD pipelines with CodePipeline and CodeBuild
- Deploy applications using CodeDeploy with Blue/Green strategy
- Create monitoring dashboards and alarms for EC2 and Lambda
- Automate infrastructure with Terraform in Jenkins pipelines
Tools: CloudFormation, CDK, CodePipeline, Terraform, Jenkins
Module 15: Machine Learning on AWS
ML Foundation 2 hours
What You Will Learn:
- Understand the ML lifecycle on AWS
- Differentiate between SageMaker, AI Services, and Bedrock
- Identify use cases for prediction, classification, NLP, and vision
Tools: SageMaker, AI Services, Bedrock
Data Preparation 2.5 hours
What You Will Learn:
- Ingest data from S3, Kinesis, and Glue
- Transform data using Glue and Data Wrangler
- Perform feature engineering and selection
- Label datasets with SageMaker Ground Truth
Tools: S3, Kinesis, Glue, SageMaker
Model Training 2.5 hours
What You Will Learn:
- Use built-in algorithms (XGBoost, Linear Learner, etc.)
- Bring Your Own Model (BYOM) to SageMaker
- Optimize models with hyperparameter tuning
- Implement distributed training with spot instances
Tools: SageMaker
Model Deployment & Monitoring 2.5 hours
What You Will Learn:
- Deploy models for real-time and batch inference
- Implement multi-model endpoints
- Monitor models for drift, bias, and explainability
- Set up A/B testing and shadow deployments
Tools: SageMaker
Module 16: AI Services
AWS AI Services 3 hours
What You Will Learn:
- Implement computer vision with Rekognition
- Perform NLP tasks with Comprehend
- Build chatbots with Lex
- Convert text to speech with Polly
- Add real-time translation with Translate
Tools: Rekognition, Comprehend, Lex, Polly, Translate
ML Security & Governance 2 hours
What You Will Learn:
- Detect bias and explain model decisions with SageMaker Clarify
- Implement encryption for data at rest and in transit
- Configure IAM roles and policies for ML workloads
- Set up audit logging with CloudTrail
Tools: SageMaker Clarify, IAM, CloudTrail
Module 17: Generative AI with Bedrock
Amazon Bedrock Fundamentals 2.5 hours
What You Will Learn:
- Understand Bedrock architecture and supported models
- Apply prompt engineering techniques
- Implement grounding for factual responses
- Compare fine-tuning vs RAG approaches
- Configure guardrails and content moderation
Tools: Bedrock, Claude, Titan, Llama
Module 18: ML Hands-On Labs
Practical ML Implementation 4 hours
What You Will Learn:
- Train and deploy an ML model with SageMaker
- Build an image moderation application
- Implement an NLP pipeline for text analysis
- Create a chatbot with Lex and Lambda integration
Tools: SageMaker, Lex, Lambda
Module 19: AI Agents & LangChain
AI Agent Fundamentals 2.5 hours
What You Will Learn:
- Understand different agent types (reactive, planning, tool-using)
- Implement memory management for conversations
- Integrate tools like APIs, search, and calculators
Advanced Prompt Engineering 2 hours
What You Will Learn:
- Create prompt templates and chains
- Implement few-shot and zero-shot prompting
- Apply context injection and grounding with RAG
LangChain with Bedrock 3 hours
What You Will Learn:
- Build LangChain agents with Bedrock models
- Use toolkits and chains (LLMChain, SequentialChain)
- Generate embeddings and implement vector search
- Integrate with OpenSearch and Pinecone
Tools: LangChain, Bedrock, OpenSearch
Module 20: MLOps & Agent Deployment
MLOps for AI Agents 2.5 hours
What You Will Learn:
- Package and version models
- Implement CI/CD for ML with SageMaker Pipelines
- Apply AgentOps: observability, evaluation, and rollback
- Set up logging, tracing, and metrics for agents
Tools: SageMaker Pipelines, GitHub Actions
Agent Deployment & Scaling 2 hours
What You Will Learn:
- Deploy agents via SageMaker endpoints or Lambda
- Integrate with API Gateway for external access
- Implement autoscaling for cost optimization
Tools: SageMaker, Lambda, API Gateway
Security for AI Workloads 2 hours
What You Will Learn:
- Configure IAM roles and policies for agents
- Implement guardrails in Bedrock
- Set up content filtering and audit logging
Tools: IAM, Bedrock, CloudTrail
Module 21: AI Agent Hands-On Labs
Advanced AI Implementation 4 hours
What You Will Learn:
- Build a RAG (Retrieval-Augmented Generation) agent
- Deploy an agent API for external consumption
- Implement a secure end-to-end AI workflow
Tools: Bedrock, LangChain, API Gateway