Uploaded August 2026 | Updated September 2026, 3 weeks ago

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In this shorts, explore the RAG Engineer Roadmap 2026 and understand the key skills required to build a career in Generative AI. Learn how RAG Engineers combine large language models, vector databases, embeddings, prompt engineering, APIs, and AI application development to create smarter AI systems that can retrieve information and generate accurate responses. Discover the roadmap to becoming a job-ready RAG Engineer and the skills you need to stay ahead in the evolving AI landscape. Watch more AI and technology career insights with Simplilearn.

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➡️ About Applied Generative AI Specialization

The Applied Gen AI Course equips learners with the skills to build AI-driven solutions. Learn to design, train, and deploy models while addressing ethics, bias, and compliance. Gain industry-relevant experience through hands-on projects to drive innovation and stay competitive in an AI-powered world.

Key Features:

✅ Get a program completion certificate from Michigan Engineering Professional Education
✅ Engage in 70+ hours of live online sessions led by industry experts
✅ Access a comprehensive curriculum covering Python, AI literacy, and GenAI principles (VAEs, GANs, and LLMs)
✅ Explore agentic frameworks and create adaptive AI agents using LangChain
✅ Implement advanced prompt engineering, RAG, and fine-tune models for domain-specific AI solutions
✅ Apply best practices for AI transparency, fairness, security, and regulatory compliance
✅ Work with 12+ modern AI tools, including OpenAI, Stable Diffusion, Microsoft Copilot, and Streamlit
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✅ Experience flexible learning with session recordings
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Skills Covered
✅ Prompt Engineering
✅ Agentic Frameworks
✅ AI Agents
✅ LangChain for Workflow Design
✅ Retrieval Augmented Generation RAG
✅ LLM Fine Tuning
✅ Stable Diffusion
✅ Variational Autoencoders VAEs
✅ Generative Adversarial Networks GANs
✅ Attention Mechanisms
✅ Transformers
✅ GenAI Application Development
✅ LLM Benchmarking
✅ GenAI Governance
✅ AI Image Generation

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