MLS-C01: AWS Certified Machine Learning Specialty Bootcamp

About this course

Unlock your path to AWS Certified Machine Learning – Specialty (MLS-C01) mastery with this comprehensive, hands-on course! Perfect for data scientists, ML engineers, and AWS professionals aiming to certify and build production-grade ML solutions on AWS.This course covers all four official exam domains with up-to-date content aligned to the latest guide:

Data Engineering (20%): Create scalable data repositories, implement ingestion pipelines (Kinesis, Firehose, Glue, EMR), orchestrate batch/streaming workloads, and transform data for ML using AWS Glue, Spark, and efficient storage (S3, EFS, databases).

Exploratory Data Analysis (24%): Sanitize datasets, handle missing values/outliers/imbalance, perform feature engineering with SageMaker Data Wrangler, and visualize/analyze data to uncover insights and detect bias early using SageMaker Clarify.

Modeling (36%): Frame business problems as ML tasks, select/train/tune models with built-in algorithms (XGBoost, DeepAR, BlazingText, Image Classification, Factorization Machines), apply distributed training, hyperparameter optimization, evaluate performance, and ensure explainability via SHAP and Debugger rules.

Machine Learning Implementation and Operations (20%): Deploy models (real-time endpoints, batch transform, multi-model, serverless), implement MLOps with SageMaker Pipelines and Model Registry, monitor drift/quality/bias (Model Monitor), secure workloads (VPC isolation, encryption, IAM), optimize costs (Spot instances, autoscaling), and maintain reliable production ML systems.

Featuring practical labs, Python code examples, real-world scenarios, 100+ exam-style MCQs, and step-by-step SageMaker workflows, you'll gain the skills to pass the MLS-C01 exam confidently before the deadline. Whether advancing your career in AI/ML, validating expertise in SageMaker/MLOps, or preparing for hi

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