MLOps Engineering on AWS: Building, Training, and Deploying Machine Learning Models
About This Program
This three-day course is designed to teach participants how to extend DevOps practices to build, train, and deploy machine learning models on AWS. The program is a combination of theory and hands-on labs, where participants will learn how to leverage the full power of AWS to create scalable and efficient ML pipelines.
What You Will Learn
- Building scalable and efficient ML pipelines using AWS services such as SageMaker, Lambda, and Step Functions.
- Automating the entire ML pipeline, from data preprocessing to model training and deployment.
- Leveraging containerization technologies to package and deploy ML models in production.
- Monitoring, debugging, and optimizing ML pipelines for performance and cost efficiency.
- Best practices for managing ML workflows, versioning models, and maintaining model accuracy.
Who This Course Is For
Developers
DevOps engineers
Data scientists
Requirements
- Prior experience with DevOps principles
- Basic knowledge of machine learning concepts
- AWS account
- Basic familiarity with AWS services such as EC2, S3, and CloudFormation
Course Syllabus
Benefits
- Practical hands-on experience with AWS services for building ML pipelines.
- In-depth knowledge of automating and optimizing ML workflows.
- Understanding of best practices for model deployment and management.
Frequently Asked Questions
This course is designed for developers, DevOps engineers, and data scientists who want to learn how to deploy and manage machine learning models using AWS. Prior experience with DevOps principles and basic knowledge of machine learning concepts are recommended.
This is an instructor-led course that combines theory with hands-on labs. Participants will have access to AWS accounts and will be guided through practical exercises designed to reinforce key concepts.
The course runs for three days, with each day consisting of approximately six hours of instruction and hands-on labs.
Participants should have prior experience with DevOps principles and basic knowledge of machine learning concepts. It is also recommended to have an AWS account and basic familiarity with AWS services such as EC2, S3, and CloudFormation.
This course is designed for developers, DevOps engineers, and data scientists with prior experience in DevOps principles and basic knowledge of machine learning concepts. It may not be suitable for absolute beginners in these areas.
