Exam Readiness- AWS Certified Machine Learning – Specialty Course Overview
Enroll for the 1-day Exam Readiness: AWS Certified Machine Learning – Specialty certification training course from this course Solutions accredited by AWS. The AWS Certified Machine Learning – Specialty exam validates your ability to design, implement, deploy, and maintain Machine Learning (ML) solutions for given business problems. In this course you will learn how to prepare for the exam by exploring the exam’s topic areas including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.
Target Audience:
This course is intended for Machine learning practitioners who are preparing to take the AWS Certified Machine Learning – Specialty exam
Learning Objectives:
After completing this course, you will be able to:
- Identify your strengths and weaknesses in each of the exam domains.
- Create a subsequent study plan to prepare for the exam.
- 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
Module 1: Exam Overview and Test-taking Strategies
- Testing center information and expectations
- Exam overview and structure
- Content domains and question breakdown
- Topics and concepts within content domains
- Question structure and interpretation techniques
- Practice exam questions
Module 2: Domain 1 – Data Engineering
- Domain 1.1: Data Repositories for machine learning
- Domain 1.2: Identify and implement a data-ingestion solution
- Domain 1.3: Identify and implement a data-transformation solution
- Walkthrough of study questions
- Domain 1 quiz
Module 3: Domain 2 – Exploratory Data Analysis
- Domain 2.1: Sanitize and prepare data for modeling
- Domain 2.2: Perform featuring engineering
- Domain 2.3: Analyze and visualize data for ML
- Walkthrough of study questions
- Domain 2 quiz
- Domain 3.1: Frame business problems as machine learning (ML) problems
- Domain 3.2: Select the appropriate model(s) for a given ML problem
- Domain 3.3: Train ML models
- Domain 3.4 Perform hyperparameter optimization
- Domain 3.5 Evaluate ML models
- Walkthrough of study questions
- Domain 3 quiz
Module 5: Domain 4 – ML Implementation and Operations
- Domain 4.1: Build ML solutions for performance, availability, scalability, resiliency, and fault tolerance
- Domain 4.2: Recommend and implement the appropriate ML services and features for a given problem
- Domain 4.3: Apply basic AWS security practices to ML solutions
- Domain 4.4: Deploy and operationalize ML solutions Walkthrough of study questions Domain 4 quiz