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Master AWS machine learning services with comprehensive preparation for the MLS-C01 exam. Practice data engineering, exploratory data analysis, modeling, and ML operations.
The AWS Certified Machine Learning - Specialty (MLS-C01) validates expertise in designing, building, training, tuning, and deploying machine learning models using AWS services. This certification demonstrates your ability to apply machine learning principles to solve real-world business problems on the AWS platform.
Exam Details: 65 questions | 180 minutes | Passing score: 750/1000 | Cost: $300 USD
The exam covers four key domains: Data Engineering (20%), Exploratory Data Analysis (24%), Modeling (36%), and ML Implementation and Operations (20%). You'll need hands-on experience with Amazon SageMaker, AWS ML services, and core machine learning concepts.
Understand the core concepts of machine learning, from supervised to unsupervised learning, and when to use each approach.
Understand how neural networks work, from perceptrons to deep learning architectures like CNNs and transformers.
Learn how machines understand and process human language, from tokenization to modern LLMs.
180 minutes
~65 questions
750 (scaled)
MLS-C01
AWS
Data collection strategies and ingestion patterns, AWS Glue for ETL and data cataloging, Amazon S3 for data lakes and storage optimization
Feature engineering and transformation techniques, Statistical analysis and hypothesis testing, Handling missing values, outliers, and imbalanced data
SageMaker built-in algorithms (XGBoost, Linear Learner, K-Means), Supervised vs unsupervised vs reinforcement learning, Model training strategies and distributed training
SageMaker endpoint deployment and auto-scaling, Batch transform for bulk inference, A/B testing with SageMaker multi-variant endpoints
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