Overview
The Amazon Web Services (AWS) authorized Exam Readiness: AWS Certified Machine Learning – Specialty helps participants prepare for the AWS Certified Machine Learning – Specialty certification exam. This credential would validate the participant’s ability to design, implement, deploy, and maintain Machine Learning (ML) solutions for given business problems. This exam readiness workshop explores the exam’s topic areas including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations. The course discusses how to interpret the exam questions in each topic area while also teaching the participants to apply the concepts being tested so that they can eliminate incorrect responses more easily.
What You'll Learn
- Identify your strengths and weaknesses in each of the exam domains
- Describe the technical topics and concepts making up each of the exam domains
- Summarize the logistics and mechanics of the certification exam and its questions
- Identify effective test-taking strategies that can be used to answer exam questions
- Create a subsequent study plan to prepare for the exam
Curriculum
Course introduction
- Testing center information and expectations
- Exam overview and structure
- Content domains and question breakdown
- Topics & concepts within content domains
- Question structure and interpretation techniques
- Practice exam questions
- Data repositories for machine learning
- Identify and implement a data ingestion solution
- Identify and implement a data transformation solution
- Walkthrough of study questions
- Sanitize and prepare data for modeling
- Perform feature engineering
- Analyze and visualize data for machine learning
- Walkthrough of study questions
- Domain 2 Quiz
- Frame business problems as machine learning problems
- Select the appropriate models for a given machine learning problem
- Train machine learning models
- Perform hyperparameter optimization
- Evaluate machine learning models
- Walkthrough of study questions
- Domain 3 Quiz
- 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
- Apply basic AWS security practices to machine learning solutions
- Deploy and operationalize machine learning solutions
- Walkthrough of study questions
- Domain 4 Quiz
comprehensive study questions
Study material
Wrap-up
Who should attend
This AWS course is intended for machine learning practitioners who are preparing to take the AWS Certified Machine Learning – Specialty exam.
Prerequisites
For this AWS course, participants are recommended to have:
- 1-2 years of hands-on experience developing, architecting, or running machine learning or deep learning workloads on the AWS cloud
- Proficiency in expressing the intuition behind basic machine learning algorithms and performing basic hyperparameter optimization
- Understanding of machine learning pipeline and its components
- Experience with machine learning and deep learning frameworks
- Understanding of and experience in model training, deployment, and operational best practices
Interested in this Course?
Certification
The Exam Readiness: AWS Certified Machine Learning – Specialty certification validates an individual’s ability to build, tune, train, and deploy machine learning models using the AWS cloud. This AWS certification is intended for individuals who perform development or a data science role. It justifies the certification holder’s ability to design, implement, deploy, and maintain machine learning (ML) solutions for a given business problem.
This AWS certification exam has 65 questions – either multiple-choice or multiple-response. Participants get 180 minutes to complete the exam. This AWS certification exam is currently offered in English, Japanese, Korean, and Simplified Chinese.
