In Part 1, you mastered the core AI vocabulary. Now, we're diving into the 10 advanced concepts that elevate a basic AI into a powerful, autonomous system that can learn, reason, and act in the real world. 🚀

We’ll talk about:

• A complete guide to 10 more advanced AI engineering concepts, from agentic systems to model optimization (Part 2).
• How AI moves beyond chatbots to become autonomous AI Agents that can take initiative and complete multi-step tasks.
• The power of MCP (Model Context Protocol), the crucial bridge that allows an AI to connect with and control external apps.
• How AI learns from feedback using Reinforcement Learning and shows its work with Chain of Thought for more accurate results.
• The secrets to making AI faster and cheaper: a look at Distillation (creating "student" models) and Quantization (compressing models for efficiency).

Keywords: AI Engineering, AI Concepts, AI Agents, MCP (Model Context Protocol), Context Engineering, Reinforcement Learning (RL), Chain of Thought (CoT), Reasoning Models, Multi-modal Models, Small Language Models (SLMs), Distillation, Quantization

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