@datascibykashi: If you want to work in AI or data science, learning RAG is becoming one of the most valuable skills. Here is the simple roadmap: 1️⃣ Python Fundamentals You need strong basics in Python for working with data and AI libraries. 2️⃣ Natural Language Processing (NLP) Understand tokenization, embeddings, and text preprocessing. 3️⃣ Vector Embeddings Learn how text becomes numerical vectors using models like sentence embeddings. 4️⃣ Vector Databases Store embeddings using tools like Pinecone, FAISS, or Weaviate. 5️⃣ Retrieval Systems Learn similarity search and document retrieval. 6️⃣ Large Language Models (LLMs) Understand how models generate responses. 7️⃣ RAG Pipeline Combine retrieval + generation to create intelligent AI systems. Many modern AI assistants, chatbots, and enterprise search tools are built using RAG. 💬 Comment Question (important for engagement): What part of this roadmap is hardest for you? A) Embeddings B) Vector Databases C) LLMs D) Building the pipeline Comment A, B, C, or D. I’ll reply to every comment. Save this post if you’re learning data science, AI, or machine learning. #creatorsearchinsights #datascience #ai #machinelearning #rag

Data Scientist | Kashi

Open In TikTok:

Region: PK

Monday 16 March 2026 14:47:52 GMT