AWS Machine Learning Certification Mastery for Cloud Professionals

Week 1: Certification Exam Review and AWS ML Overview

Review the structure of the AWS Machine Learning certification exam and gain an understanding of key AWS ML services.

• activity: Certification Exam Structure Overview
• discussion points:

  • How the AWS ML exam is structured
  • Key services to focus on
• reading assignment: AWS Machine Learning Certification Guide, Chapter 1

Week 2: Machine Learning Fundamentals in AWS

Dive into the basics of machine learning and its application in AWS.

• activity: Lab: Building a Model in SageMaker
• discussion points:

  • Supervised vs Unsupervised Learning
  • Training models in SageMaker
• reading assignment: AWS Machine Learning Certification Guide, Chapter 2

Week 3: Data Engineering and Preparation

Learn how to clean, normalize, and prepare data using AWS Glue and Lake Formation.

• activity: Lab: Building an ETL Pipeline with AWS Glue
• discussion points:

  • How to clean data for ML
  • Using AWS Glue and Lake Formation
• reading assignment: AWS Machine Learning Certification Guide, Chapter 3

Week 4: Building and Training ML Models with SageMaker

Learn to build, train, and deploy models using SageMaker.

• activity: Lab: Training a Customer Churn Model
• discussion points:

  • How to train models in SageMaker
  • Best practices for model deployment
• reading assignment: AWS Machine Learning Certification Guide, Chapter 4

Week 5: AI Services for Text and Image Processing

Explore Amazon Rekognition, Polly, and other AI services for speech, text, and image processing.

• activity: Lab: Image Recognition and Text-to-Speech with Rekognition and Polly
• discussion points:

  • Using Rekognition for image analysis
  • Text-to-speech using Polly
• reading assignment: AWS Machine Learning Certification Guide, Chapter 5

Week 6: Optimizing Machine Learning Models

Learn about hyperparameter tuning and model optimization.

• activity: Lab: Optimizing a Model with SageMaker
• discussion points:

  • Tuning hyperparameters
  • Using SageMaker Debugger for model performance
• reading assignment: AWS Machine Learning Certification Guide, Chapter 6

Week 7: Security and Compliance for Machine Learning

Understand the importance of security, compliance, and governance in AWS ML.

• activity: Discussion: Securing ML Pipelines in AWS
• discussion points:

  • IAM roles for ML workflows
  • Data encryption in AWS
• reading assignment: AWS Machine Learning Certification Guide, Chapter 7

Week 8: Final Project: Building a Full AWS ML Solution

Apply your knowledge to build an end-to-end machine learning pipeline using AWS.

• activity: Lab: End-to-End ML Solution for Customer Churn Prediction
• discussion points:

  • Integrating SageMaker, Glue, and Polly
  • End-to-end ML workflows
• reading assignment: AWS Machine Learning Certification Guide, Chapter 8

Week 9: Exam Preparation and Review

Focus on exam-style questions, review of key concepts, and final practice exams.

• activity: Mock Exam and Certification Review
• discussion points:

  • Final review of key AWS ML concepts
  • Exam preparation strategies
• reading assignment: AWS Machine Learning Certification Guide, Chapter 9

Who should take this course?

Cloud professionals at different skill levels who are aiming to get certified in AWS Machine Learning and transition into AI/ML roles.

What is the main focus of the course?

The course is focused on helping participants pass the AWS Machine Learning certification exam. It provides a deep dive into AWS ML tools and services with exam-specific preparation techniques.

What are the prerequisites?

Basic understanding of cloud computing concepts and experience with AWS is recommended, but not mandatory.

How is the course structured?

The course includes live sessions, certification review, hands-on labs, personalized AI tutor support, and mock exams.

Will I be prepared for the AWS Machine Learning certification exam?

Yes, the course is specifically designed to prepare students for the AWS Machine Learning certification exam. It includes exam simulations, mnemonics for quick recall, and hands-on labs for real-world experience.