Overview
The AWS Certified Machine Learning – Specialty Training equips you with advanced machine learning skills using AWS services, preparing you thoroughly for the AWS Certified Machine Learning – Specialty (MLS-C01) certification exam and enabling you to build, train, deploy, and optimize ML models at scale on AWS.
What is AWS Certified Machine Learning – Specialty Certification?
This certification validates your expertise in creating and managing ML solutions on the AWS platform using SageMaker, data pipelines, and advanced ML algorithms while ensuring scalable, secure, and cost-effective deployments.
Why Choose This Certification?
- Globally recognized AWS certification for ML professionals
- Demonstrates your ability to implement ML solutions on AWS infrastructure
- Enhances credibility for ML Engineer, Data Scientist, and AI Specialist roles
- Opens opportunities for advanced projects in AI and ML across industries
AWS MLS-C01 Exam Details:
- Exam Code: MLS-C01
- 65 multiple-choice and multiple-response questions
- Duration: 3 hours
- Covers four domains: Data Engineering, Exploratory Data Analysis, Modeling, and Machine Learning Implementation & Operations
Additional Benefits:
- Hands-on labs for real-world ML pipeline deployment on AWS
- Scenario-based practice for practical understanding
- Enhances your practical readiness for high-demand ML roles
Certificate
Features
- Fully aligned with the latest AWS MLS-C01 exam objectives
- Hands-on labs for real AWS ML implementation experience
- Practice quizzes and mock exams for confident preparation
- Real-world projects for practical understanding
- Lifetime access to course resources (if online)
- Certificate of completion for your professional record
- Training delivered by AWS-certified ML professionals
Target audiences
- Data Scientists and Machine Learning Engineers using AWS
- AI Specialists and Solution Architects designing ML solutions
- Software Engineers looking to advance in ML and AWS cloud
- Professionals seeking to validate their expertise in AWS-based machine learning
Requirements
- Foundational knowledge of AWS services (AWS Certified Cloud Practitioner or equivalent experience recommended)
- Basic understanding of machine learning algorithms and data science principles
- Programming experience in Python or a similar language is beneficial
Curriculum
- 6 Sections
- 18 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Data Engineering on AWS3
- Exploratory Data Analysis3
- Modeling3
- Machine Learning Implementation and Operations3
- Exam Preparation3
- Practical Applications3
FAQs
It is a certification by AWS validating your skills in designing, building, deploying, and maintaining ML solutions on AWS.
It is recommended to have foundational AWS knowledge (Cloud Practitioner or Associate level), but it is not mandatory.
Preparation typically takes 3–4 months of structured learning and hands-on practice for most professionals.
Yes, the training includes practical labs for building, deploying, and optimizing ML models on AWS using SageMaker and related services.
Yes, this training fully aligns with the latest MLS-C01 exam structure and AWS updates, ensuring up-to-date preparation.
Instructor
