AWS Certified Cloud Practitioner (CLF-C02): Deployment, Migration, and AI
Field | Description |
Purpose | To provide a comprehensive overview of the AWS application ecosystem, covering modern development tools, migration workflows, and the vast suite of AI, ML, and Analytics services. |
Audience | Technical professionals looking to understand how to build, move, and enhance applications using advanced AWS automation and intelligent services. |
Role | Junior Developers, DevOps Associates, Data Analysts, and Cloud Migration Specialists. |
Domain | Application Integration / AI & Machine Learning / Cloud Migration. |
Skill Level | Beginner (Fundamental). |
Style | A high-velocity survey of advanced services featuring multiple "In Action" labs for AI services (Polly, Transcribe, Rekognition) and infrastructure automation. |
Duration | 2 Days. |
Related Technologies | Amazon Bedrock, SageMaker, AWS Lambda, SNS/SQS, CloudFormation, AWS Snow Family, and Amazon Athena. |
Course Description
AWS Certified Cloud Practitioner (CLF-C02): Deployment, Migration, and AI explores the "modernization" tools of the AWS Cloud. This module moves beyond basic infrastructure to focus on how applications are built, integrated, and made "smart." You will learn to decouple systems using messaging services like SNS and SQS, automate infrastructure using CloudFormation, and explore the AWS Snow Family for physical data migration. A significant portion of the course is dedicated to the AI/ML and Analytics stack, where you will gain hands-on experience with managed AI services for vision, speech, and text analysis, as well as serverless analytics tools like Amazon Athena.
Who is this course for
This course is intended for:
Modern Developers: Those who need to understand CI/CD, Infrastructure as Code, and how to integrate managed AI into their apps.
Migration Leads: Professionals tasked with identifying the right tools (DataSync, Snowball, Migration Hub) to move data and applications to AWS.
Aspiring Data & AI Practitioners: Individuals looking for a broad survey of the AWS data lake and machine learning ecosystem.
CLF-C02 Candidates: This covers the "Technology" and "Cloud Concepts" domains of the exam, specifically focusing on the higher-level managed services.
Course Objectives
Application Integration: Differentiate between SNS (Pub/Sub) and SQS (Queuing) to build decoupled, resilient architectures.
Infrastructure as Code: Understand the benefits of AWS CloudFormation and Elastic Beanstalk for automated and managed deployments.
Migration Strategy: Identify the correct tools for physical and over-the-wire data transfer, including the Snow Family and AWS DataSync.
Analytics Deep-Dive: Contrast big data tools like Amazon EMR, Redshift, and Kinesis for various processing requirements.
AI/ML Practicality: Experience "AI-as-a-Service" through labs with Amazon Rekognition (vision), Polly (speech), and Transcribe (text), and understand the role of Amazon SageMaker.
Prerequisites
Required Foundation: Completion of CLF-C02: Cloud Foundations and CLF-C02: Storage, Networking, and Databases.
Technical Interest: A basic interest in how automation and Artificial Intelligence are changing modern business operations.
Course outline
Section 1: Development, Messaging, and Deployment Technology and Services
What Is CI/CD?
AWS Development Tools
Lab: Working with AWS CloudShell and the AWS Command Line Interface (AWS CLI)
Lab: Using AWS Cloud9
Understanding AWS CodeArtifact
Decoupling Application Components
Introducing Amazon Simple Notification Service (SNS)
Create and Subscribe to an AWS SNS Topic
Amazon Simple Queue Service (SQS)
Standard and FIFO Queues
Short Polling vs Long Polling
What Is Amazon Simple Email Service (SES)?
Introducing Amazon EventBridge
Understanding Step Functions
Deploying Infrastructure as Code with AWS CloudFormation
Create a DynamoDB Table Using CloudFormation
Is AWS Elastic Beanstalk?
Lab: Deploying an Application Using Elastic Beanstalk
Lab: Using AWS X-Ray to Identify Performance Issues
Development, Messaging, and Deployment Exam Tips - Part 1
Development, Messaging, and Deployment Exam Tips - Part 2
Development, Messaging, and Deployment Technology and Services Quiz
Section 2: Migration and Transfer Technology and Services
Introducing the AWS Snow Family
Identifying Database Migration Tools
Exploring the AWS Transfer Family
AWS DataSync
Understanding AWS Application Discovery Service
Introducing AWS Application Migration Service
Discovering AWS Migration Hub
Migration and Transfer Exam Tips
Migration and Transfer Technology and Services Quiz
Section 3: Artificial Intelligence, Machine Learning, and Analytics Technology and Services
Amazon Redshift and Redshift Serverless
What Is Amazon Kinesis?
Exploring Kinesis Data Firehose
What Is Amazon Athena?
Lab: Using Athena to Query Data
Introducing AWS Glue
Exploring AWS Data Exchange
Understanding Amazon Elastic Map Reduce (EMR)
is Amazon OpenSearch?
Exploring Managed Streaming for Apache Kafka (Amazon MSK)
Understanding Amazon QuickSight
Machine Learning With Amazon SageMaker
What Is Amazon Kendra?
Understanding Amazon Lex
Lab: Using Amazon Polly
Introducing Amazon Comprehend
Amazon Textract, Amazon Transcribe, and Amazon Translate
Lab: Using Amazon Transcribe
Lab: Amazon Rekognition in Action
Artificial Intelligence, Machine Learning, and Analytics Exam Tips - Part 1
Artificial Intelligence, Machine Learning, and Analytics Exam Tips - Part 2
Artificial Intelligence and Machine Learning Technology and Services Quiz