An AWS Machine Learning (Specialty) exam helps candidates who usually fulfil a data science or
It shows an individual’s competence in designing, implementing, deploying and maintaining machine
learning solutions for applicable problems.
Why Take The AWS Machine Learning (Specialty) Course?
Your certification places you at the front of the line.
Passing the exam will allow you to attain an industry-recognized merit from AWS that says: you
know what you’re doing. It proves to your employer that you have the necessary skills and
knowledge to earn top dollar when you work for them.
Increase Your Salary:
- The average starting salary of an AWS Machine Learning (Specialty) in 2019 was around
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 & 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
Domain 1: Data Engineering 20%
Domain 2: Exploratory Data Analysis 24%
Domain 3: Modeling 36%
Domain 4: Machine Learning Implementation and Operations 20%
AWS Certified Machine Learning – Specialty (MLS-C01)
Domain 1: Data Engineering
1.1 Create data repositories for machine learning.
1.2 Identify and implement a data-ingestion solution.
1.3 Identify and implement a data-transformation solution.
Domain 2: Exploratory Data Analysis
2.1 Sanitize and prepare data for modeling.
2.2 Perform feature engineering.
2.3 Analyze and visualize data for machine learning.
Domain 3: Modeling
3.1 Frame business problems as machine learning problems.
3.2 Select the appropriate model(s) for a given machine learning problem.
3.3 Train machine learning models.
3.4 Perform hyperparameter optimization.
3.5 Evaluate machine learning models.
Domain 4: Machine Learning Implementation and Operations
4.1 Build machine learning solutions for performance, availability, scalability, resiliency, and
4.2 Recommend and implement the appropriate machine learning services and features for a
4.3 Apply basic AWS security practices to machine learning solutions.
4.4 Deploy and operationalize machine learning solutions
Prepare for your exam:
The best way to prepare is with first-hand experience. Taking advantage of the opportunities that
Phoenix TS provides will assist you with gathering all the knowledge and skills you’ll need for
Phoenix TS AWS Certified Machine Learning – Learning Pathways
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