edX
edXAdvanced: Generative AI for Developers
1k studentsINTERMEDIATEEnglish
Korshub's take
Generative AI deployment at scale demands both technical depth and ethical guardrails. This advanced course builds your understanding of transformer architectures, attention mechanisms, and the BERT/Gemini models reshaping industry—then equips you to deploy them responsibly.
You'll master image generation and multimodal AI (inspecting documents with Gemini), implement fairness and bias mitigation, ensure interpretability and transparency, and hardwire privacy into your systems. Learn MLOps for generative AI using Vertex AI Studio, apply retrieval-augmented generation (RAG) for grounded outputs, and design AI agents that are both powerful and trustworthy. This is where technical excellence and ethical responsibility converge.
For: ML engineers, AI product leaders, teams shipping generative AI in production.
About this course
Develop a deeper technical understanding of generative AI models and architectures, including the attention mechanism, encoder-decoder architecture, transformer models, and the BERT model. ,Build practical skills in creating models for tasks like image generation and image captioning, and learn to leverage Gemini Multimodality to inspect rich documents. ,Learn the critical principles and techniques to ensure the ethical deployment of AI, including mitigating fairness and bias, ensuring interpretability and transparency, and maintaining privacy and safety. ,Deploy and manage generative AI solutions in production by prototyping and launching models using tools like Vertex AI Studio and apply MLOps best practices for the deployment and management of generative AI at scale. ,Apply advanced search and data retrieval technologies using vector embeddings, semantic search, and retrieval-augmented generation (RAG) to create AI agents.
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