Module 1: Foundations of Cloud & AWS

• Understand global AWS infrastructure (Regions, AZs, Edge Locations)

• Set up your AWS account with IAM best practices

• Explore core services: EC2, S3, RDS, Lambda, VPC

• Learn shared responsibility and basic security on AWS

Module 2: Python for Data & ML on AWS

• Refresh Python basics for data analysis

• Work with NumPy, Pandas, and Matplotlib

• Use Jupyter notebooks in Amazon SageMaker Studio

• Load, clean, and prepare real-world datasets

Module 3: Data Engineering on AWS

• Store and query data with S3, Athena, and Glue

• Build simple ETL pipelines for ML

• Understand data lakes vs. data warehouses

• Design data pipelines that are secure and cost‑efficient

Module 4: Core Machine Learning Concepts

• Supervised vs. unsupervised learning

• Train/test split, cross‑validation, and evaluation metrics

• Overfitting, underfitting, and regularization

• Hands-on labs with regression and classification models

Module 5: Building Models with Amazon SageMaker

• Use built‑in algorithms and pre‑built containers

• Train, tune, and deploy models with SageMaker

• Work with SageMaker Autopilot for automated ML

• Monitor model performance and costs

Module 6: Deep Learning on AWS

• Intro to neural networks, CNNs, and RNNs

• Use GPU instances for training

• Build image and text models with SageMaker

• Optimize training jobs for speed and cost

Module 7: Generative AI on AWS

• Understand foundation models and LLMs

• Explore Amazon Bedrock and related services

• Build a simple GenAI app (chatbot or content generator)

• Discuss responsible AI, safety, and governance

Module 8: MLOps & Model Deployment

• CI/CD for ML workflows on AWS

• Use SageMaker Pipelines and Model Registry

• Automate retraining and deployment

• Implement monitoring and alerting for models in production

Module 9: Exam Preparation & Practice

• Map each module to AWS certification exam domains

• Review key services, patterns, and best practices

• Solve full‑length practice questions and case studies

• Get tips for exam strategy, time management, and next steps

By the end of this program, learners will be ready to build, deploy, and manage real‑world AI/ML solutions on AWS and confidently sit for the AWS AI/ML certification exam.