AWS Crash Course for Beginners Curriculum

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Curriculum

AWS Crash Course for Beginners

Learn essential AWS services without the certification pressure. Perfect for developers and IT pros who want hands-on cloud skills fast. Build real projects on AWS infrastructure.

Duration: 12 Weeks
Level: Beginner
Study Time: 4 hours/week + labs
School: Cloud & DevOps
⏱️ 12 Weeks📊 Beginner☁️ Hands-On Labs

Welcome to AWS Crash Course for Beginners! 🎓

This curriculum for AWS Crash Course for Beginners follows a Bloom-aligned progression from foundational concepts to confident application, with weekly evidence, labs, and portfolio outputs matched to beginner expectations.

Each week advances from comprehension and application toward evaluation and creation, ensuring progressive learning and capstone readiness.

Your success is our priority. By the end of the programme, you will be able to explain and deploy core AWS building blocks confidently and use that foundation to move into architecture, DevOps, or cloud support specializations. You will graduate with a professionally curated portfolio that demonstrates scope, depth, and delivery quality. You will graduate with a professionally curated portfolio that demonstrates scope, depth, and delivery quality. You will graduate with a professionally curated portfolio that demonstrates scope, depth, and delivery quality. You will graduate with a professionally curated portfolio that demonstrates scope, depth, and delivery quality.

Prerequisites

  • Experience designing system architectures with distributed components and resilience patterns
  • Hands-on practice with Infrastructure-as-Code, cloud service models (IaaS/PaaS/SaaS), and networking basics
  • Understanding of auto-scaling, load balancing, and cloud cost optimization tradeoffs
  • Familiarity with at least one major cloud console (AWS, Azure, or GCP) and basic CLI usage

Essential Resources

  • Cloud architecture reference implementations and Well-Architected Framework reviews
  • Infrastructure-as-Code templates and cloud service comparison matrices
  • Cost optimization playbooks and resilience validation runbooks

Complementary Courses

Cloud Networking

Master virtual networks, security groups, and multi-region routing

DevOps & Infrastructure Automation

Deepen CI/CD pipeline integration and infrastructure drift detection

Cloud Cost Optimization

Learn resource tagging, rightsizing, and multi-cloud cost analysis

Learning Roadmap

  • Early Weeks: Core cloud services, networking fundamentals, and basic deployments
  • Middle Weeks: Advanced architectures, multi-region deployment, and disaster recovery
  • Late Weeks: Cost optimization, governance frameworks, and production readiness

Detailed Weekly Curriculum

Each week includes outcomes and practical lab work aligned to the curriculum structure.

Week 1

Cloud Computing & AWS Basics

4 hours + labs
Learning Outcomes
  • Identify the principles of Cloud Computing & AWS Basics and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Explain Cloud Computing & AWS Basics in a guided scenario using realistic tools, constraints, and quality gates.
  • Apply trade-offs, risks, and decision points for Cloud Computing & AWS Basics, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for Cloud Computing & AWS Basics with measurable success criteria and next actions.
Lab Exercise
  • Implement a production-style Cloud Computing & AWS Basics setup using versioned config/code and environment controls.
  • Run validation gates for Cloud Computing & AWS Basics covering reliability, security, and rollback readiness.
  • Publish Cloud Computing & AWS Basics execution evidence with logs, metrics, and troubleshooting notes.
Week 2

EC2: Virtual Servers in the Cloud

4 hours + labs
Learning Outcomes
  • Identify the principles of EC2: Virtual Servers in the Cloud and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Explain EC2: Virtual Servers in the Cloud in a guided scenario using realistic tools, constraints, and quality gates.
  • Apply trade-offs, risks, and decision points for EC2: Virtual Servers in the Cloud, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for EC2: Virtual Servers in the Cloud with measurable success criteria and next actions.
Lab Exercise
  • Implement a production-style EC2: Virtual Servers in the Cloud setup using versioned config/code and environment controls.
  • Run validation gates for EC2: Virtual Servers in the Cloud covering reliability, security, and rollback readiness.
  • Publish EC2: Virtual Servers in the Cloud execution evidence with logs, metrics, and troubleshooting notes.
Week 3

S3: Object Storage

4 hours + labs
Learning Outcomes
  • Identify the principles of S3: Object Storage and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Explain S3: Object Storage in a guided scenario using realistic tools, constraints, and quality gates.
  • Apply trade-offs, risks, and decision points for S3: Object Storage, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for S3: Object Storage with measurable success criteria and next actions.
Lab Exercise
  • Design and execute a concrete S3: Object Storage build in AWS Crash Course for Beginners with a clear acceptance checklist.
  • Validate S3: Object Storage with objective tests and quality controls before review.
  • Deliver S3: Object Storage artifacts with reproducible steps and operational notes.
Week 4

RDS: Managed Databases

4 hours + labs
Learning Outcomes
  • Identify the principles of RDS: Managed Databases and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Explain RDS: Managed Databases in a guided scenario using realistic tools, constraints, and quality gates.
  • Apply trade-offs, risks, and decision points for RDS: Managed Databases, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for RDS: Managed Databases with measurable success criteria and next actions.
Lab Exercise
  • Build a practical RDS: Managed Databases workflow with source-to-output transformation steps.
  • Validate RDS: Managed Databases quality and performance with objective checks and tuning updates.
  • Deliver reproducible RDS: Managed Databases outputs (dashboard/report/notebook) with run instructions.
Week 5

VPC: Virtual Private Cloud

4 hours + labs
Learning Outcomes
  • Apply the principles of VPC: Virtual Private Cloud and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Analyze VPC: Virtual Private Cloud in a guided scenario using realistic tools, constraints, and quality gates.
  • Evaluate trade-offs, risks, and decision points for VPC: Virtual Private Cloud, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for VPC: Virtual Private Cloud with measurable success criteria and next actions.
Lab Exercise
  • Implement a working VPC: Virtual Private Cloud topology with explicit segmentation and traffic intent.
  • Validate allowed and denied flows for VPC: Virtual Private Cloud with repeatable connectivity tests.
  • Document fault scenarios and recovery steps for VPC: Virtual Private Cloud operations.
Week 6

Load Balancing & Auto Scaling

4 hours + labs
Learning Outcomes
  • Apply the principles of Load Balancing & Auto Scaling and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Analyze Load Balancing & Auto Scaling in a guided scenario using realistic tools, constraints, and quality gates.
  • Evaluate trade-offs, risks, and decision points for Load Balancing & Auto Scaling, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for Load Balancing & Auto Scaling with measurable success criteria and next actions.
Lab Exercise
  • Design and execute a concrete Load Balancing & Auto Scaling build in AWS Crash Course for Beginners with a clear acceptance checklist.
  • Validate Load Balancing & Auto Scaling with objective tests and quality controls before review.
  • Deliver Load Balancing & Auto Scaling artifacts with reproducible steps and operational notes.
Week 7

Lambda: Serverless Computing

4 hours + labs
Learning Outcomes
  • Apply the principles of Lambda: Serverless Computing and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Analyze Lambda: Serverless Computing in a guided scenario using realistic tools, constraints, and quality gates.
  • Evaluate trade-offs, risks, and decision points for Lambda: Serverless Computing, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for Lambda: Serverless Computing with measurable success criteria and next actions.
Lab Exercise
  • Design and execute a concrete Lambda: Serverless Computing build in AWS Crash Course for Beginners with a clear acceptance checklist.
  • Validate Lambda: Serverless Computing with objective tests and quality controls before review.
  • Deliver Lambda: Serverless Computing artifacts with reproducible steps and operational notes.
Week 8

CloudFormation & Infrastructure as Code

4 hours + labs
Learning Outcomes
  • Apply the principles of CloudFormation & Infrastructure as Code and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Analyze CloudFormation & Infrastructure as Code in a guided scenario using realistic tools, constraints, and quality gates.
  • Evaluate trade-offs, risks, and decision points for CloudFormation & Infrastructure as Code, then record rationale for stakeholder review.
  • Document a portfolio-ready architecture decision record for CloudFormation & Infrastructure as Code with measurable success criteria and next actions.
Lab Exercise
  • Implement a production-style CloudFormation & Infrastructure as Code setup using versioned config/code and environment controls.
  • Run validation gates for CloudFormation & Infrastructure as Code covering reliability, security, and rollback readiness.
  • Publish CloudFormation & Infrastructure as Code execution evidence with logs, metrics, and troubleshooting notes.
Week 9

Monitoring & Security

4 hours + labs
Learning Outcomes
  • Analyze the principles of Monitoring & Security and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Evaluate Monitoring & Security in a guided scenario using realistic tools, constraints, and quality gates.
  • Create trade-offs, risks, and decision points for Monitoring & Security, then record rationale for stakeholder review.
  • Defend a portfolio-ready architecture decision record for Monitoring & Security with measurable success criteria and next actions.
Lab Exercise
  • Implement baseline controls for Monitoring & Security and verify enforcement on target systems.
  • Run assessment/scanning for Monitoring & Security and prioritize findings by exploitability and impact.
  • Close critical findings for Monitoring & Security and publish re-test evidence.
Week 10

Container Services: ECS & ECR

4 hours + labs
Learning Outcomes
  • Analyze the principles of Container Services: ECS & ECR and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Evaluate Container Services: ECS & ECR in a guided scenario using realistic tools, constraints, and quality gates.
  • Create trade-offs, risks, and decision points for Container Services: ECS & ECR, then record rationale for stakeholder review.
  • Defend a portfolio-ready architecture decision record for Container Services: ECS & ECR with measurable success criteria and next actions.
Lab Exercise
  • Design and execute a concrete Container Services: ECS & ECR build in AWS Crash Course for Beginners with a clear acceptance checklist.
  • Validate Container Services: ECS & ECR with objective tests and quality controls before review.
  • Deliver Container Services: ECS & ECR artifacts with reproducible steps and operational notes.
Week 11

DevOps on AWS

4 hours + labs
Learning Outcomes
  • Analyze the principles of DevOps on AWS and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Evaluate DevOps on AWS in a guided scenario using realistic tools, constraints, and quality gates.
  • Create trade-offs, risks, and decision points for DevOps on AWS, then record rationale for stakeholder review.
  • Defend a portfolio-ready architecture decision record for DevOps on AWS with measurable success criteria and next actions.
Lab Exercise
  • Implement a production-style DevOps on AWS setup using versioned config/code and environment controls.
  • Run validation gates for DevOps on AWS covering reliability, security, and rollback readiness.
  • Publish DevOps on AWS execution evidence with logs, metrics, and troubleshooting notes.
Week 12

Capstone Project & Best Practices

4 hours + labs
Learning Outcomes
  • Analyze the principles of Capstone Project & Best Practices and link them to course outcomes with scaffolded guidance and beginner-safe checkpoints.
  • Evaluate Capstone Project & Best Practices in a guided scenario using realistic tools, constraints, and quality gates.
  • Create trade-offs, risks, and decision points for Capstone Project & Best Practices, then record rationale for stakeholder review.
  • Defend a portfolio-ready architecture decision record for Capstone Project & Best Practices with measurable success criteria and next actions.
Lab Exercise
  • Design and execute a concrete Capstone Project & Best Practices build in AWS Crash Course for Beginners with a clear acceptance checklist.
  • Validate Capstone Project & Best Practices with objective tests and quality controls before review.
  • Deliver Capstone Project & Best Practices artifacts with reproducible steps and operational notes.

Capstone Projects

Project 1: AWS Crash Course for Beginners Foundation Build

Deliver a concrete foundation implementation covering the first phase of the curriculum.

  • Implement and validate Cloud Computing & AWS Basics.
  • Integrate EC2: Virtual Servers in the Cloud with reusable workflow standards.
  • Publish evidence for S3: Object Storage with test and quality artifacts.

Project 2: AWS Crash Course for Beginners Integrated Systems Build

Combine mid-program competencies into a production-style integrated workflow.

  • Build an end-to-end flow around VPC: Virtual Private Cloud and Load Balancing & Auto Scaling.
  • Add controls, observability, and rollback paths for reliability.
  • Document architecture decisions and trade-offs tied to Lambda: Serverless Computing.

Project 3: AWS Crash Course for Beginners Capstone Delivery

Ship a portfolio-ready capstone with measurable outcomes and stakeholder-ready presentation.

  • Deliver a complete implementation centered on Monitoring & Security.
  • Validate readiness for Container Services: ECS & ECR using objective acceptance checks.
  • Present final defense and roadmap based on DevOps on AWS outcomes.