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This video explains a complete and future-proof Generative AI roadmap designed for 2026 and beyond. Starting from core technical requirements, optional Machine Learning and Deep Learning foundations, and moving step-by-step into Generative AI fundamentals, this roadmap clearly shows the correct learning order for building a strong AI career. You’ll learn how to progress through LLMs, SLMs, and Multimodal models, advance into fine-tuning techniques, build production-grade systems using RAG (Retrieval-Augmented Generation), and design intelligent agent-based AI systems. The roadmap also covers MCP (Model Context Protocol), cloud services for GenAI, real-world deployment strategies, and finally end-to-end AI-powered projects that integrate everything into production-ready applications. This roadmap is perfect for beginners, developers, working professionals, and AI engineers who want clarity instead of confusion and want to stay relevant in the AI industry for the next 3–5 years. 👉 Watch till the end to understand what to learn, what is optional, and what truly matters for building real-world Generative AI applications. #llm #embedding #ai #futureai #generativeai #genai #textgeneration #ragapp #langchain #programminglogic #python #chatbot #openai #gpt #langchainj #rag #crossencoder #transformers #multiretriever #ragfusion #advancerag #llamaindex #langchain #gemini #google #rag #LCEL #langgraph #aiagent #react #aiagents #generativeai #airoadmap #ailearning #aiengineering #aiengineer #llm #slm #multimodalai #finetune #finetuning #aiagents #agenticai #multiagentsystems #multiagent #rag #modelcontextprotocol #aicloud #bedrock #azureopenai #vertexai #llmops #aiskills #sunnysavita Don't miss out; learn with me! P.S. Don't forget to like and subscribe for more AI content! Roadmap Link: https://github.com/sunnysavita10/Generative-AI-Indepth-Basic-to-Advance/blob/main/GenAI%20Syllabus-deatail.pdf Interview Question Doc Link: https://docs.google.com/document/d/1IS3ltUepSRX9q1Le9NcRgup9bLfKkFpjzAwxp9sT31U/edit?usp=sharing Interview Answer link: https://drive.google.com/file/d/1NACwvTHVftEIdHZuZmGzC3JQLXqzHUan/view?usp=sharing End-to-End-Langgraph-Course: https://github.com/sunnysavita10/langgraph-end-to-end Multimodel RAG Playlis: https://www.youtube.com/watch?v=7CXJWnHI05w&list=PLQxDHpeGU14D6dm0rmAXhdLeLYlX2zk7p&pp=gAQBiAQB RAG detailed Playlist: https://www.youtube.com/watch?v=wTVTkOb3SZc&list=PLQxDHpeGU14Blorx3Ps1eZJ4XvKET1_vx&pp=gAQBiAQB GenAI Foundation Playlist: https://www.youtube.com/watch?v=ajWheP8ZD70&list=PLQxDHpeGU14D7NiPgqxC9qhKkx4jMQcDk&pp=gAQBiAQB Connect with me on Social Media- LinkedIn : https://www.linkedin.com/in/sunny-savita/ One to One Call: https://topmate.io/sunny_savita10 GitHub : https://github.com/sunnysavita10 Telegram : https://t.me/aimldlds
