What will you learn in AWS Generative AI and AI Agents with Amazon Bedrock Professional Certificate course
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Understand the architecture and working principles of Generative AI models and large language models (LLMs).
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Build, fine-tune, and deploy Generative AI applications using AWS services.
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Work with foundation models via AWS tools and APIs.
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Implement prompt engineering and retrieval-augmented generation (RAG).
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Integrate AI capabilities into scalable cloud-native applications.
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Apply monitoring, security, and responsible AI best practices in production.
Program Overview
Foundations of Generative AI for Developers
⏳ 3–4 weeks
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Learn how transformer-based models and LLMs function.
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Understand embeddings, tokenization, and model inference basics.
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Explore real-world developer-focused AI use cases.
Building Applications with AWS AI Services
⏳ 4–5 weeks
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Use AWS services to access and deploy foundation models.
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Integrate AI APIs into backend and cloud applications.
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Understand cloud architecture patterns for AI-powered apps.
Prompt Engineering and Advanced Techniques
⏳ 3–4 weeks
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Design effective prompts for various development scenarios.
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Implement RAG pipelines for knowledge-grounded responses.
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Explore fine-tuning and model customization strategies.
Deployment, Monitoring, and Responsible AI
⏳ 3–4 weeks
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Deploy scalable AI applications in AWS environments.
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Monitor performance, latency, and costs.
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Apply governance, compliance, and security controls.
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Job Outlook
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Highly relevant for Software Developers, Cloud Engineers, and ML Engineers.
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Strong demand for developers who can build AI-enabled cloud applications.
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Valuable for roles such as Generative AI Developer, Cloud AI Engineer, and MLOps Engineer.
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Aligns well with AWS certification pathways and AI/cloud-focused career tracks.
