Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction
- Understanding machine learning with SageMaker
- Machine learning algorithms
Overview of AWS SageMaker Features
- AWS and cloud computing
- Models development
Setting up AWS SageMaker
- Creating an AWS account
- IAM admin user and group
Familiarizing with SageMaker Studio
- UI overview
- Studio notebooks
Preparing Data Using Jupyter Notebooks
- Notebooks and libraries
- Creating a notebook instance
Training a Model with SageMaker
- Training jobs and algorithms
- Data and model parallel trainings
- Post-training bias analysis
Deploying a Model in SageMaker
- Model registry and model monitor
- Compiling and deploying models with Neo
- Evaluating model performance
Cleaning Up Resources
- Deleting endpoints
- Deleting notebook instances
Troubleshooting
Summary and Conclusion
Requirements
- Experience with application development
- Familiarity with Amazon Web Services (AWS) Console
Audience
- Data scientists
- Developers
21 Hours
Testimonials (5)
Trainer had good grasp of concepts
Josheel - Verizon Connect
Course - Amazon Redshift
The practice part.
Radu - Ness Digital Engineering
Course - AWS: A Hands-on Introduction to Cloud Computing
The training was more practical
Siphokazi Biyana - Vodacom SA
Course - Kubernetes on AWS
The trainer knew exactly what they were speaking about.
Madumetsa Msomi - BMW
Course - AWS DevOps Engineers
All good, nothing to improve