MLS-C01 – AWS Certified Machine Learning - Specialty Exam

About this course

Unlock your path to becoming an AWS Certified Machine Learning – Specialty expert with this comprehensive MLS-C01 – AWS Certified Machine Learning Specialty course! Designed for aspiring ML engineers, data scientists, and AWS professionals, this hands-on training equips you to design, build, train, tune, deploy, optimize, and maintain scalable machine learning solutions on the AWS Cloud.Dive deep into the four core exam domains:Data Engineering (~20%): Master ingesting, storing, and transforming massive datasets using Amazon S3, Kinesis, Glue, Feature Store, and streaming pipelines for real-time and batch ML workflows.Exploratory Data Analysis (~24%): Learn advanced EDA techniques with SageMaker Data Wrangler, visualization tools, handling imbalanced data, missing values, outliers, and bias detection using SageMaker Clarify.Modeling (~36%): Explore AWS built-in algorithms (XGBoost, DeepAR, BlazingText, Image Classification, Factorization Machines), distributed training, hyperparameter tuning, overfitting mitigation, explainability (SHAP), and probabilistic forecasting.ML Implementation and Operations (~20%): Build production-grade MLOps with SageMaker Pipelines, Model Monitor for drift detection, real-time endpoints, batch transform, multi-model endpoints, autoscaling, security (VPC-only, encryption), and cost optimization via Spot instances.Packed with practical labs, real-world scenarios, 100+ exam-style MCQs, code examples in Python, and step-by-step SageMaker workflows, you'll gain the confidence to pass the MLS-C01 exam on your first attempt. Whether you're preparing for certification, advancing your career in AI/ML, or implementing enterprise ML solutions, this course covers everything from data pipelines and feature engineering to bias mitigation, model monitoring, and secure deployment.Key benefits:

Course objectives

• prepare for the MLS-C01 exam
• advance career opportunities in machine learning and AWS