Online Course
Introduction to AWS Cloud

An entry-level AWS course that introduces core cloud concepts through real-world scenarios. Learn how systems are designed, secured, and scaled using AWS services. With guided and hands-on lessons, it builds practical skills and architectural insight for confident cloud design.

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  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Skill level:

Basic

Duration:

2 hours
  • Lessons (2 hours)
  • Practice exams (20 minutes)

CPE credits:

4
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org

Accredited

certificate

What you learn

  • Cloud Fundamentals: Learn core cloud computing concepts & AWS global structure.
  • IAM: Create secure access management with users, groups, roles & AWS policies.
  • VPC: Create secure isolated networks using subnets & routing controls.
  • Storage: Design scalable solutions with Amazon S3 & other AWS storage services.
  • Databases: Set up & manage SQL/NoSQL systems with RDS, Aurora & DynamoDB.
  • Compute: Deploy EC2 virtual servers & create serverless apps with AWS Lambda.

Topics & tools

Amazon Web ServicesCloud ComputingAws

Your instructor

Course OVERVIEW

Description

CPE Credits: 4 Field of Study: Specialized Knowledge
Delivery Method: QAS Self Study

This course offers a practical, scenario-driven introduction to cloud architecture using AWS. Designed for learners who want to understand how real systems are built and operated, it guides you through the core services, design principles, and decision-making strategies that power modern cloud solutions.

You’ll explore how AWS services work together to support secure, scalable, and cost-effective applications. Each module is built around realistic challenges—from launching a media platform to supporting a civic tech initiative—so you’re not just learning features, you’re solving problems.

What you’ll learn:

  • How cloud systems are planned, deployed, and scaled using AWS
  • Core AWS services: IAM, VPC, EC2, S3, Lambda, DynamoDB, RDS
  • Networking fundamentals: subnets, routing, NAT gateways, security groups
  • Identity and access management: roles, policies, and least privilege
  • Storage and compute: choosing services based on performance, durability, and cost
  • Serverless and event-driven design with Lambda and API Gateway
  • Data architecture basics: relational vs NoSQL, analytics with Athena and Redshift
  • Cost optimization and architectural tradeoffs
  • Real-world case studies and guided walkthroughs to reinforce each concept

Who it’s for: This course is ideal for aspiring cloud engineers, developers and anyone looking to build a strong foundation in AWS. No prior cloud experience is required—just curiosity and a willingness to learn by doing.

By the end of the course, you’ll be able to design and explain cloud solutions with clarity, troubleshoot common issues, and make smart decisions that balance performance, security, and cost.

Prerequisites

  • Access to aws.amazon.com and a free AWS account

Advanced preparation

Curriculum

51 lessons 29 exercises 2 exams
  • 1. Overview of Cloud Computing & AWS
    18 min

    This section introduces students to the foundational concepts and practical skills needed to begin working confidently with AWS. Learners will:

    • Understand cloud computing fundamentals, including the shift from on-premise infrastructure to scalable, on-demand cloud services.
    • Explore AWS’s global infrastructure—Regions and Availability Zones—and learn how to choose deployment locations based on compliance, latency, and cost.
    • Set up their own AWS account step-by-step, gaining hands-on experience with identity verification, billing setup, and console access.
    • Grasp AWS’s pricing models, including pay-as-you-go and Savings Plans, and learn how to manage costs using tools like Cost Explorer.
    • Apply the AWS Well-Architected Framework to design secure, resilient, cost-effective, and sustainable cloud solutions.

    By the end of this section, students will be equipped to navigate the AWS Console, understand core infrastructure principles, and make informed decisions about cloud architecture and budgeting.

    18 min

    This section introduces students to the foundational concepts and practical skills needed to begin working confidently with AWS. Learners will:

    • Understand cloud computing fundamentals, including the shift from on-premise infrastructure to scalable, on-demand cloud services.
    • Explore AWS’s global infrastructure—Regions and Availability Zones—and learn how to choose deployment locations based on compliance, latency, and cost.
    • Set up their own AWS account step-by-step, gaining hands-on experience with identity verification, billing setup, and console access.
    • Grasp AWS’s pricing models, including pay-as-you-go and Savings Plans, and learn how to manage costs using tools like Cost Explorer.
    • Apply the AWS Well-Architected Framework to design secure, resilient, cost-effective, and sustainable cloud solutions.

    By the end of this section, students will be equipped to navigate the AWS Console, understand core infrastructure principles, and make informed decisions about cloud architecture and budgeting.

  • 2. User Management with IAM
    27 min

    This section equips students with a deep understanding of AWS Identity and Access Management (IAM), focusing on secure, scalable access control strategies. Learners will:

    • Grasp the core purpose of IAM and its role in managing authentication and authorization across AWS services.
    • Create and manage IAM users and groups, applying least privilege principles to organize access efficiently.
    •  Write and attach IAM policies using JSON syntax, learning how to define granular permissions and evaluate policy effects.
    • Explore IAM roles for cross-service access, temporary credentials, and secure delegation between AWS resources.
    •  Apply best practices like MFA enforcement and avoiding root user reliance to build secure environments.

    By the end of this section, students will be able to design and implement robust IAM strategies that support secure operations and scalable team collaboration.

    27 min

    This section equips students with a deep understanding of AWS Identity and Access Management (IAM), focusing on secure, scalable access control strategies. Learners will:

    • Grasp the core purpose of IAM and its role in managing authentication and authorization across AWS services.
    • Create and manage IAM users and groups, applying least privilege principles to organize access efficiently.
    •  Write and attach IAM policies using JSON syntax, learning how to define granular permissions and evaluate policy effects.
    • Explore IAM roles for cross-service access, temporary credentials, and secure delegation between AWS resources.
    •  Apply best practices like MFA enforcement and avoiding root user reliance to build secure environments.

    By the end of this section, students will be able to design and implement robust IAM strategies that support secure operations and scalable team collaboration.

  • 3. Networking on AWS
    21 min

    This section guides students through the architecture and security of Amazon Virtual Private Cloud (VPC), empowering them to design isolated, secure, and scalable network environments. Learners will:

    • Understand the purpose and structure of VPCs, including CIDR blocks, IP addressing, and default vs. custom VPCs.
    • Dive into subnets—public and private—and configure them for controlled access to resources.
    • Explore route tables and learn how traffic is directed within and between subnets, with hands-on practice.
    • Configure security groups and network ACLs to enforce fine-grained traffic control, comparing stateful and stateless behavior.
    • Implement VPC peering to enable secure communication between VPCs across accounts or regions.

    By the end of this section, students will be able to build and secure multi-tier architectures using VPC components and apply best practices for segmentation and access control.

    21 min

    This section guides students through the architecture and security of Amazon Virtual Private Cloud (VPC), empowering them to design isolated, secure, and scalable network environments. Learners will:

    • Understand the purpose and structure of VPCs, including CIDR blocks, IP addressing, and default vs. custom VPCs.
    • Dive into subnets—public and private—and configure them for controlled access to resources.
    • Explore route tables and learn how traffic is directed within and between subnets, with hands-on practice.
    • Configure security groups and network ACLs to enforce fine-grained traffic control, comparing stateful and stateless behavior.
    • Implement VPC peering to enable secure communication between VPCs across accounts or regions.

    By the end of this section, students will be able to build and secure multi-tier architectures using VPC components and apply best practices for segmentation and access control.

  • 4. Core Services: Storage
    16 min

    This section introduces students to AWS storage services, with a focus on Amazon S3 and its practical applications. Learners will:

    • Understand the range of AWS storage offerings and their use cases, including object, block, and file storage.
    • Explore Amazon S3’s key features such as durability, scalability, and global accessibility.
    • Create and configure S3 buckets, including naming conventions, region selection, and access settings.
    • Upload and manage objects within S3 buckets, using the console.
    • Compare S3 storage classes and select appropriate options based on access frequency and cost-efficiency.
    • Implement lifecycle policies to automate transitions between storage classes and manage data retention.
    • Gain exposure to other AWS storage services like EBS, EFS, and Glacier, understanding when and why to use each.

    By the end of this section, students will be able to architect storage solutions that balance performance, cost, and data management needs.

    16 min

    This section introduces students to AWS storage services, with a focus on Amazon S3 and its practical applications. Learners will:

    • Understand the range of AWS storage offerings and their use cases, including object, block, and file storage.
    • Explore Amazon S3’s key features such as durability, scalability, and global accessibility.
    • Create and configure S3 buckets, including naming conventions, region selection, and access settings.
    • Upload and manage objects within S3 buckets, using the console.
    • Compare S3 storage classes and select appropriate options based on access frequency and cost-efficiency.
    • Implement lifecycle policies to automate transitions between storage classes and manage data retention.
    • Gain exposure to other AWS storage services like EBS, EFS, and Glacier, understanding when and why to use each.

    By the end of this section, students will be able to architect storage solutions that balance performance, cost, and data management needs.

  • 5. Core Services: Databases
    13 min

    This section introduces students to AWS database services, focusing on both relational and NoSQL options, along with hands-on experience in provisioning and querying. Learners will:

    • Understand the differences between relational and non-relational databases, and when to use each.
    • Explore Amazon RDS and Amazon Aurora, including automated backups and replication.
    • Launch and configure RDS and Aurora instances, connect to them securely, and execute SQL scripts for data manipulation.
    • Practice writing and running SQL queries to create tables, insert data, and retrieve results.
    • Learn about Amazon DynamoDB, its key-value and document data model, and use cases for high-performance NoSQL workloads.
    • Perform hands-on tasks with DynamoDB, including table creation, item insertion, and query operations.

    By the end of this section, students will be able to choose appropriate AWS database services based on workload requirements, deploy and connect to managed databases, and perform basic data operations using SQL and DynamoDB.

    13 min

    This section introduces students to AWS database services, focusing on both relational and NoSQL options, along with hands-on experience in provisioning and querying. Learners will:

    • Understand the differences between relational and non-relational databases, and when to use each.
    • Explore Amazon RDS and Amazon Aurora, including automated backups and replication.
    • Launch and configure RDS and Aurora instances, connect to them securely, and execute SQL scripts for data manipulation.
    • Practice writing and running SQL queries to create tables, insert data, and retrieve results.
    • Learn about Amazon DynamoDB, its key-value and document data model, and use cases for high-performance NoSQL workloads.
    • Perform hands-on tasks with DynamoDB, including table creation, item insertion, and query operations.

    By the end of this section, students will be able to choose appropriate AWS database services based on workload requirements, deploy and connect to managed databases, and perform basic data operations using SQL and DynamoDB.

  • 6. Core Services: Compute
    8 min

    This section introduces students to AWS compute services, focusing on both virtual server provisioning and serverless architecture. Learners will:

    • Understand the role of compute in cloud environments and the differences between traditional and serverless models.
    • Launch and configure Amazon EC2 instances, including selecting AMIs, instance types and security groups.
    • Connect to EC2 instances
    • Explore AWS Lambda as a serverless compute service, including its event-driven model and integration with other AWS services.
    • Build and deploy Lambda functions

    By the end of this section, students will be able to provision virtual machines, deploy serverless functions, and choose appropriate compute options based on workload characteristics.

    8 min

    This section introduces students to AWS compute services, focusing on both virtual server provisioning and serverless architecture. Learners will:

    • Understand the role of compute in cloud environments and the differences between traditional and serverless models.
    • Launch and configure Amazon EC2 instances, including selecting AMIs, instance types and security groups.
    • Connect to EC2 instances
    • Explore AWS Lambda as a serverless compute service, including its event-driven model and integration with other AWS services.
    • Build and deploy Lambda functions

    By the end of this section, students will be able to provision virtual machines, deploy serverless functions, and choose appropriate compute options based on workload characteristics.

  • 7. Course exam
    60 min
    60 min

9 in 10

people walk away career-ready

with practical data and AI skills.

9 in 10

of our graduates landed a new AI & data job

after enrollment

$29,000

average salary increase

after moving to an AI and data science career

ACCREDITED certificates

Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global institutions.

Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities employers value most.

  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Certificates are included with the Self-study learning plan.

A LinkedIn profile mockup on a mobile screen showing Parker Maxwell, a Certified Data Analyst, with credentials from 365 Data Science listed under Licenses & Certification. A 365 Data Science Certificate of Achievement awarded to Parker Maxwell for completing the Data Analyst career track, featuring accreditation badges and a gold “Verified Certificate” seal.

How it WORKS

  • Lessons
  • Exercises
  • Projects
  • Practice exams
  • AI mock interviews

Lessons

Learn through short, simple lessons—no prior experience in AI or data science needed.

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Exercises

Reinforce your learning with mini recaps, hands-on coding, flashcards, fill-in-the-blank activities, and other engaging exercises.

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Projects

Tackle real-world AI and data science projects—just like those faced by industry professionals every day.

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Practice exams

Track your progress and solidify your knowledge with regular practice exams.

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AI mock interviews

Prep for interviews with real-world tasks, popular questions, and real-time feedback.

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Student REVIEWS

A collage of student testimonials from 365 Data Science learners, featuring profile photos, names, job titles, and quotes or video play icons, showcasing diverse backgrounds and successful career transitions into AI and data science roles.