Advanced Developing on AWS Course
- Duration: 24 hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
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Course Overview
The Practical Data Science with Amazon SageMaker Course is designed to help organizations build practical, end-to-end data science capabilities using AWS-managed machine learning services. This course focuses on designing, building, training, tuning, and deploying machine learning models using Amazon SageMaker. With a structured and governance-aligned approach, the program enables enterprise teams to operationalize data science workflows efficiently while ensuring scalability, security, and consistency across projects.
Course Details
- Strengthens advanced application development skills on AWS
- Improves scalability, security, and performance of cloud-native applications
- Aligns development practices with globally recognized AWS frameworks
- Ensures consistent learning delivery across enterprise teams
- Enhances productivity through hands-on advanced development scenarios
- Supports structured readiness for enterprise application modernization initiatives
- Open to corporate professionals and application development teams
- Suitable for intermediate to advanced participants
- Recommended for teams building and maintaining applications on AWS
- Prior experience with AWS core services and application development preferred
- Familiarity with cloud-native design patterns is beneficial
- Corporate sponsorship or group participation encouraged
- Access to a digital learning platform required
- Design and build advanced cloud-native applications on AWS
- Implement event-driven, decoupled, and serverless architectures
- Apply best practices for security, scalability, and fault tolerance
- Optimize application performance and cost efficiency
- Gain hands-on experience through structured practical modules
- Improve collaboration between development and platform teams
- Align application development strategies with organizational objectives
- Advanced AWS application architecture patterns
- Designing event-driven and serverless applications
- Application integration using messaging and streaming services
- Implementing security and identity best practices for applications
- Managing application scalability and performance
- Monitoring, logging, and troubleshooting applications
- CI/CD pipelines and deployment strategies
- Practical labs and real-world development scenarios
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