Overview
Master Cloud-Based Machine Learning on AWS
This course will teach critical skills to design and deploy scalable ML solutions. The core skills covered are:
- Data Preparation: Ingest, transform, and clean data using SageMaker
- Pipeline Automation: Build and deploy end-to-end ML workflows
- Solution Management: Monitor, secure, and optimize AWS-based ML systems
It offers hands-on AWS training that is ideal for software developers, data scientists, ML engineers, and DevOps professionals, this course blends theory with practical projects to help you design production-ready ML architectures, automate CI/CD pipelines for efficient deployment, implement security best practices for cloud-based systems.
You can find additional resources here: https://bitbucket.org/awsdevguru/awsmlassoc/src/main/
Related Learning:
- Sign up for more live trainings by Nick Garner
About the Instructor
Nick Garner, CCIE No. 17871, is a Solutions Integration Architect with Cisco Systems supporting customers in large-scale network design. He has deployed and supported large-scale data center designs for prominent clients in the San Francisco Bay area and works with Amazon Web Services daily. Prior to Cisco, he spent some time with a Cisco partner, Denali Advanced Integration, and is also a founder of several IoT companies that operate exclusively in AWS.
Skill Level:
- Intermediate to advanced
Course requirement:
- None
About Pearson Video Training
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