@datascibykashi: Today I’m breaking down the exact roadmap I’m following to become an AI Engineer — step-by-step, beginner to advanced. If you’re confused about where to start or what to learn next… this is for you. 💡 What’s inside this roadmap: 1️⃣ Math Foundation: Linear algebra, calculus, probability & statistics. 2️⃣ Programming: Python + NumPy, Pandas, Matplotlib, Scikit-Learn. 3️⃣ ML Basics: Regression, classification, clustering, evaluation metrics. 4️⃣ Deep Learning: Neural networks, CNNs, RNNs, Transformers. 5️⃣ AI Engineering Skills: MLOps, Docker, APIs, vector databases, LangChain, model deployment. 6️⃣ Projects: End-to-end ML pipelines, LLM apps, recommender systems, chatbots, AI agents. 7️⃣ Portfolio + Job Prep: GitHub, resume, LeetCode, system design for AI. 🤖 AI Engineering is the future, and if you start today, you’ll thank yourself next year. ❓ QUESTION FOR YOU (boosts comments): Which step are you stuck on OR which topic should I cover next — LLMs, MLOps, or Neural Networks? Comment below 👇 — I’ll make the next video based on your replies! 🔥 Save this roadmap. Follow for daily ML + AI content! #aiengineer #ai #creatorsearchinsights #datascience #educatoraward

Data Scientist | Kashi

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Wednesday 03 December 2025 13:40:00 GMT