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Weitere Amazon Web Services Zertifizierungen
Amazon Web Services
- AWS Certified Cloud Practitioner
- AWS Certified Solutions Architect – Associate
- AWS Certified Developer – Associate
- AWS Certified SysOps Administrator – Associate
- AWS Certified Solutions Architect – Professional
- AWS Certified DevOps Engineer - Professional
- AWS Certified Advanced Networking - Specialty
- AWS Certified Alexa Skill Builder - Specialty
- AWS Certified Data Analytics - Specialty
- AWS Certified Database - Specialty
- AWS Certified Machine Learning - Specialty
- AWS Certified Security - Specialty

AWS Certified Machine Learning - Specialty (ACMLS)
The AWS Certified Machine Learning - Specialty certification is intended for individuals who perform a development or data science role. It validates a candidate's ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems.
Abilities Validated by the Certification
- Select and justify the appropriate ML approach for a given business problem
- Identify appropriate AWS services to implement ML solutions
- Design and implement scalable, cost-optimized, reliable, and secure ML solutions
Recommended Knowledge and Experience
- 1-2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud
- The ability to express the intuition behind basic ML algorithms
- Experience performing basic hyperparameter optimization
- Experience with ML and deep learning frameworks
- The ability to follow model-training best practices
- The ability to follow deployment and operational best practices
Prerequisites
There is no better preparation than hands-on experience. There are many relevant AWS Training courses and other resources to assist you with acquiring additional knowledge and skills to prepare for certification. Please review the exam guide for information about the competencies assessed on the certification exam.
Recommended training for this certification
Data Scientist
- The Elements of Data Science (elearning)
- Data Science Capstone: Real World ML Decisions (elearning)
- Machine Learning Data Readiness (elearning)
- Developing Machine Learning Applications (elearning)
- Practical Data Science with Amazon SageMaker (PDSASM)
- Machine Learning Pipeline on AWS (ML-PIPE)
- Machine Learning Security (elearning)
- Exam Readiness: AWS Certified Machine Learning - Specialty (ERMLS)
Developer
- ML Building Blocks: Services and Terminology (elearning)
- Process Model: CRISP-DM on the AWS Stack (elearning)
- The Elements of Data Science (elearning)
- Developing Machine Learning Applications (elearning)
- Practical Data Science with Amazon SageMaker (PDSASM)
- Machine Learning Pipeline on AWS (ML-PIPE)
- Machine Learning Security (elearning)
- Exam Readiness: AWS Certified Machine Learning - Specialty (ERMLS)
Optional:
- Math for Machine Learning (elearning)
- Linear and Logistic Regression (elearning)
- Speaking Of : Machine Translation and NLP (elearning)
- Seeing Clearly: Computer Vision Theory (elearning)
Exams
AWS Certified MachineLearning–Specialty Exam (MLS-C01)