AWS Certified Machine Learning Specialty 2023 – Hands On!
AWS machine learning certification preparation – learn SageMaker, feature engineering, data engineering, modeling & more
Created by Sundog Education by Frank Kane, Stephane Maarek | AWS Certified Cloud Practitioner, Solutions Architect, Developer | 10.5 hours on-demand video course
[ Updated for 2023’s latest SageMaker features and new AWS ML Services. Happy learning! ]
Nervous about passing the AWS Certified Machine Learning – Specialty exam (MLS-C01)? You should be! There’s no doubt it’s one of the most difficult and coveted AWS certifications. A deep knowledge of AWS and SageMaker isn’t enough to pass this one – you also need deep knowledge of machine learning, and the nuances of feature engineering and model tuning that generally aren’t taught in books or classrooms. You just can’t prepare enough for this one.
This certification prep course is taught by Frank Kane, who spent nine years working at Amazon itself in the field of machine learning. Frank took and passed this exam on the first try, and knows exactly what it takes for you to pass it yourself. Joining Frank in this course is Stephane Maarek, an AWS expert and popular AWS certification instructor on Udemy.
What you’ll 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
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