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CODE: NAI21
DURATION: 3 Days | 5 Days | 10 Days
CERTIFICATIONS: CPD
This course introduces participants to the powerful AI and machine learning tools available on Amazon Web Services (AWS). It provides practical guidance on how to build, train, and deploy ML models using AWS services such as SageMaker, Rekognition, Comprehend, and Lex. Delegates will explore data preparation, model development, and automation workflows in a cloud environment. Through the course participants will acquire the in-demand skills needed to develop scalable AI solutions and integrate intelligent features into applications using AWS cloud infrastructure.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand basic AI and machine learning concepts.
Use AWS services like SageMaker for ML tasks.
Prepare and process data for machine learning.
Build and deploy scalable ML models on AWS.
Train, evaluate, and tune machine learning models.
Monitor and maintain ML models in production.
Apply business and cost considerations to ML projects.
Implement security and compliance on AWS ML services.
Gain hands-on experience with AWS ML tools.
At the end of this course, you’ll understand:
This course is designed for data scientists, ML engineers, cloud developers, and IT professionals looking to apply machine learning using AWS services. It is also ideal for business analysts, technical leads, and solution architects who want to integrate AI capabilities into cloud-based applications. Participants should have a basic understanding of Python and cloud computing environments.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
