Who should take the Amazon MLS exam
Candidates who have the following should take this exam:
- Identify appropriate AWS services to implement ML solutions
- Select and justify the appropriate ML approach for a given business problem
- Design and implement scalable, cost-optimized, reliable, and secure ML solutions
If a candidate wants significant improvement in career growth needs enhanced knowledge, skills, and talents. TThe AWS Certified Solutions Architect - Associate examination is intended for individuals who perform a solutions architect role and have one or more years of hands-on experience designing available, cost-efficient, fault-tolerant, and scalable distributed systems on AWS.
It asks for following experience:
- Experience with ML and deep learning frameworks
- 1-2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud
- The ability to follow model-training best practices
- Experience performing basic hyperparameter optimization
- The ability to follow deployment and operational best practices
- The ability to express the intuition behind basic ML algorithms
Understanding functional and technical aspects of AWS Certified Machine Learning Specialty Exam Machine Learning Implementation and Operations
The following will be dicussed here:
- Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance
- Recommend and implement the appropriate machine learning services and features for a given problem
- Deploy and operationalize machine learning solutions
- Apply basic AWS security practices to machine learning solutions
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Amazon MLS-C01 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Modeling | 32–38% | - Specialized models
|
| Topic 2: Machine Learning Operations | 15–20% | - Monitoring and maintenance
|
| Topic 3: Exploratory Data Analysis | 22–28% | - Feature engineering
|
| Topic 4: Data Engineering | 20–25% | - Data ingestion
|
