AWS Certified Machine Learning – Specialty Training
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Course Highlights
- Instructor-led Online Training
- Project Based Learning
- Certified & Experienced Trainers
- Course Completion Certificate
- Lifetime e-Learning Access
- 24x7 After Training Support
AWS Certified Machine Learning – Specialty Training Course Overview
The AWS Certified Machine Learning – Specialty course by Multisoft Systems provides a comprehensive pathway for professionals looking to advance their expertise in machine learning on the AWS platform. Designed for individuals with foundational knowledge in ML and AWS, this training program covers a broad spectrum of essential skills, from data engineering and model building to deployment and optimization within the AWS ecosystem. Participants will delve into topics like data preprocessing, feature engineering, and model tuning, leveraging AWS's machine learning services such as Amazon SageMaker, AWS Glue, and Amazon Rekognition. The course emphasizes hands-on experience, allowing learners to build, train, and deploy scalable ML models directly on AWS. Key aspects such as model evaluation, troubleshooting, and performance optimization are also included to ensure participants gain a holistic understanding of machine learning workflows on AWS.
This program is ideal for data scientists, developers, and machine learning engineers aiming to become certified in AWS Machine Learning Specialty, equipping them with practical skills to solve real-world business challenges. By the end of the course, participants will be well-prepared for the AWS Certified Machine Learning – Specialty exam, ready to apply AWS’s powerful ML capabilities to innovate and drive success within their organizations.
Instructor-led Training Live Online Classes
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AWS Certified Machine Learning – Specialty Training Course curriculum
Curriculum Designed by Experts
The AWS Certified Machine Learning – Specialty course by Multisoft Systems provides a comprehensive pathway for professionals looking to advance their expertise in machine learning on the AWS platform. Designed for individuals with foundational knowledge in ML and AWS, this training program covers a broad spectrum of essential skills, from data engineering and model building to deployment and optimization within the AWS ecosystem. Participants will delve into topics like data preprocessing, feature engineering, and model tuning, leveraging AWS's machine learning services such as Amazon SageMaker, AWS Glue, and Amazon Rekognition. The course emphasizes hands-on experience, allowing learners to build, train, and deploy scalable ML models directly on AWS. Key aspects such as model evaluation, troubleshooting, and performance optimization are also included to ensure participants gain a holistic understanding of machine learning workflows on AWS.
This program is ideal for data scientists, developers, and machine learning engineers aiming to become certified in AWS Machine Learning Specialty, equipping them with practical skills to solve real-world business challenges. By the end of the course, participants will be well-prepared for the AWS Certified Machine Learning – Specialty exam, ready to apply AWS’s powerful ML capabilities to innovate and drive success within their organizations.
- Understand foundational machine learning concepts and how they apply to AWS services.
- Learn to prepare, clean, and process datasets for training on AWS.
- Develop skills in feature engineering to improve model performance.
- Gain hands-on experience with Amazon SageMaker for model building, training, and deployment.
- Master AWS tools for data engineering, such as AWS Glue and Amazon Athena.
- Learn model tuning techniques, including hyperparameter optimization, to enhance accuracy.
- Understand model evaluation metrics and performance assessment on AWS.
- Troubleshoot common issues in machine learning workflows on AWS.
Course Prerequisite
- Basic understanding of machine learning concepts and algorithms
- Familiarity with Python programming
Course Target Audience
- Data Scientists
- Machine Learning Engineers
- AI Developers
- Data Engineers
- Solutions Architects
- IT Professionals with ML knowledge
- AWS Practitioners focusing on ML
- Business Analysts interested in ML on AWS
Course Content
- The AWS Certified Machine Learning Specialty Exam
- Study Guide Features
- AWS Certified Machine Learning Specialty Exam Objectives
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- Amazon Rekognition
- Amazon Textract
- Amazon Transcribe
- Amazon Translate
- Amazon Polly
- Amazon Lex
- Amazon Kendra
- Amazon Personalize
- Amazon Forecast
- Amazon Comprehend
- Amazon CodeGuru
- Amazon Augmented AI
- Amazon SageMaker
- AWS Machine Learning Devices
- Summary
- Exam Essentials
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- Storage
- Amazon VPC
- AWS Lambda
- AWS Step Functions
- AWS RoboMaker
- Summary
- Exam Essentials
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- Feature Engineering Concepts
- Feature Engineering Tools on AWS
- Summary
- Exam Essentials
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- Common ML Algorithms
- Local Training and Testing
- Remote Training
- Distributed Training
- Monitoring Training Jobs
- Debugging Training Jobs
- Hyperparameter Optimization
- Summary
- Exam Essentials
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- Deployment for AI Services
- Deployment for Amazon SageMaker
- Advanced Deployment Topics
- Summary
- Exam Essentials
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- Integration with On-Premises Systems
- Integration with Cloud Systems
- Integration with Front-End Systems
- Summary
- Exam Essentials
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- Security and AWS
- Secure SageMaker Environments
- AI Services Security
- Summary
- Exam Essentials
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- Reliability on AWS
- Change Management for ML
- Failure Management for ML
- Summary
- Exam Essentials
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- Common Design Principles
- Cost Optimization for ML Workloads
- Summary
- Exam Essentials
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- New Services and Features Related to AI Services
- New Features Related to Amazon SageMaker
- Summary
- Exam Essentials
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AWS Certified Machine Learning – Specialty Training (MCQ) Assessment
This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :
- User-friendly interface for easy navigation
- Secure login and authentication measures to protect data
- Automated scoring and grading to save time
- Time limits and countdown timers to manage duration.
AWS Certified Machine Learning – Specialty Corporate Training
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Certification Training Achievements: Recognizing Professional Expertise
Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :
- Globally recognized certificate
- Course ID & Course Name
- Certificate with Date of Issuance
- Name and Digital Signature of the Awardee
AWS Certified Machine Learning – Specialty Training Trainer Profile
20+ Years Experienced
Our AWS Certified Machine Learning – Specialty Training Corporate & Certification Program trainers bring 13+ years of proven industry expertise, delivering practical insights aligned with real project environments.
Trained 3150+ Professionals
Our expert trainers have successfully trained 3350+ professionals through structured, real-time training programs designed for industry readiness and career growth.
Certified Experts & Real-Time Project Learning
Build strong practical skills through live project-based training sessions led by certified industry experts with real-world experience.
Hands-on Learning Approach
Gain practical exposure through real-time scenarios, industry case studies, and hands-on assignments that simulate actual project challenges.
Certification Training Guidance
Receive expert support to prepare effectively, practice strategically, and confidently achieve globally recognized certification success.
Customized Training Delivery
Flexible training approach tailored to individual learning goals, skill levels, and evolving industry requirements for maximum effectiveness.
AWS Certified Machine Learning – Specialty Training FAQ's
This certification validates advanced expertise in building, training, and deploying machine learning models on AWS, focusing on practical, scalable solutions.
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