Exam Readiness: AWS CertifiedMachine Learning – Specialty
Duration : 4 Hours
Exam Readiness: AWS CertifiedMachine Learning – Specialty Course Overview:
The AWS Certified Machine Learning – Specialty exam validates your ability to design, implement, deploy, and maintain Machine Learning (ML) solutions for given business problems. Join this half-day, advanced level training to 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.
The course reviews how to interpret exam questions in each topic area and teaches you how to apply the concepts being tested so that you can more easily eliminate incorrect responses.
Topics in the course will address each of the exam’s four subject domains: 1) Data Engineering, 2) Exploratory Data Analysis, 3) Modeling, and 4) Machine Learning Implementation and Operations.
Course level: Advanced
Intended audience
This course is intended for:
- Machine learning practitioners who are preparing to take the AWS Certified Machine Learning – Specialty exam
Module 0: Course Introduction
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
Module 4: Domain 3 – Modeling
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
Module 6: Comprehensive Study Questions
Module 7: Study Material
Module 8: Wrap-up
Exam Readiness: AWS CertifiedMachine Learning – Specialty Course Prerequisites
We recommend that attendees of this course have:
- 1-2 years of hands-on experience developing, architecting, or running ML/deep learning workloads on the AWS cloud
- Proficiency expressing the intuition behind basic machine learning algorithms and performing basic hyper parameter optimization
- Understanding of the machine learning pipeline and its components
- Experience with machine learning and deep learning frameworks
Discover the perfect fit for your learning journey
Choose Learning Modality
Live Online
- Convenience
- Cost-effective
- Self-paced learning
- Scalability
Classroom
- Interaction and collaboration
- Networking opportunities
- Real-time feedback
- Personal attention
Onsite
- Familiar environment
- Confidentiality
- Team building
- Immediate application
Training Exclusives
This course comes with following benefits:
- Practice Labs.
- Get Trained by Certified Trainers.
- Access to the recordings of your class sessions for 90 days.
- Digital courseware
- Experience 24*7 learner support.
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