Developing Generative AI Applications on AWS Course
- Duration: 16 Hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
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Course Overview
The Developing Generative AI Applications on AWS Course focuses on building end-to-end generative AI applications using AWS-native services. The course covers application architecture, integration of foundation models, prompt engineering techniques, orchestration workflows, and deployment considerations. Through hands-on labs and scenario-driven learning, participants gain practical experience in developing scalable, secure, and responsible generative AI applications. This training supports organizations seeking to move from experimentation to real-world generative AI application development on AWS.
Course Details
- Design and develop generative AI applications on AWS
- Apply prompt engineering and model interaction techniques
- Integrate foundation models into real-world applications
- Build scalable, secure, and production-ready AI solutions
- Understand responsible AI, governance, and security considerations
- Strengthen readiness for advanced AI and cloud application development roles
- Open to developers, cloud engineers, and AI practitioners
- Suitable for intermediate and advanced participants
- Basic programming experience is recommended
- Familiarity with AWS core services is beneficial
- Understanding of AI or machine learning concepts is helpful
- Ideal for teams building AI-powered applications on AWS
- Access to digital learning platforms required
- No mandatory prior certification required
- Architect generative AI applications using AWS services
- Integrate foundation models into application workflows
- Implement prompt engineering and response optimization
- Build APIs and application backends for AI-powered features
- Apply security, governance, and responsible AI principles
- Deploy and manage generative AI applications at scale
- Translate business use cases into functional AI solutions
- Generative AI application architecture on AWS
- Foundation models and model access patterns
- Prompt engineering and application orchestration
- Building AI-powered APIs and user experiences
- Data handling, security, and governance considerations
- Monitoring, optimization, and cost considerations
- Deployment patterns and scalability strategies
- Enterprise generative AI application scenarios
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