AWS Certified Machine Learning Specialty 2025 - Hands On!

AWS machine learning certification preparation - learn SageMaker, generative AI, data engineering, modeling & more

4.62 (15427 reviews)

Udemy

platform

English

language

IT Certification

What you will learn

What to expect on the AWS Certified Machine Learning Specialty exam

Amazon SageMaker's built-in machine learning algorithms (XGBoost, BlazingText, Object Detection, etc.)

Feature engineering techniques, including imputation, outliers, binning, and normalization

High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more

Data engineering with S3, Glue, Kinesis, and DynamoDB

Exploratory data analysis with scikit_learn, Athena, Apache Spark, and EMR

Deep learning and hyperparameter tuning of deep neural networks

Automatic model tuning and operations with SageMaker

L1 and L2 regularization

Applying security best practices to machine learning pipelines

Course Gallery

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Comidoc Review

Our Verdict

This course offers an invaluable foundation for those looking to pass the AWS Certified Machine Learning Specialty exam and serves as a vital resource for understanding essential machine learning concepts in an AWS context. Its knowledgeable instructors navigate students through various crucial topics, including Amazon SageMaker algorithms, feature engineering, exploratory data analysis, and deep learning. Be prepared for a fast-paced course that may require revisiting certain sections or self-paced study to solidify understanding.

What We Liked

Comprehensive coverage of AWS Certified Machine Learning Specialty exam topics.
Knowledgeable instructors who effectively explain essential concepts like SageMaker algorithms, feature engineering techniques, and data engineering.
Well-organized sections allowing for efficient learning.
Ideal course for those pursuing the AWS Machine Learning certification or looking to bolster their understanding of various machine learning areas within AWS.

Potential Drawbacks

The fast pace may challenge beginners in machine learning; previous experience could be helpful—plan to revisit topics.
Limited hands-on exercises and shorter quizzes might require additional self-paced practice or further study.
Some users find data engineering sections light on explanation, suggesting the need for extra research.