{"id":14533,"date":"2026-03-05T10:55:59","date_gmt":"2026-03-05T02:55:59","guid":{"rendered":"https:\/\/www.novel086.top\/?p=14533"},"modified":"2026-03-05T10:56:02","modified_gmt":"2026-03-05T02:56:02","slug":"ai-study-plan5","status":"publish","type":"post","link":"https:\/\/www.novel086.top\/index.php\/2026\/03\/05\/ai-study-plan5\/","title":{"rendered":"AI\u5e94\u7528\u5f00\u53d1\u4e94\u9636\u6bb5\u5b66\u4e60\u8def\u7ebf"},"content":{"rendered":"\n

\u60f3\u8981\u6210\u4e3a\u4e00\u540d\u201c\u719f\u6089AI\u5e94\u7528\u4e0e\u5f00\u53d1\u201d\u7684\u89d2\u8272\uff0c\u4f60\u9700\u8981\u7ecf\u5386\u4ece\u6df1\u5ea6\u4f7f\u7528\u8005\uff08Power User\uff09\u5230\u5f00\u53d1\u8005\uff08Developer\uff09<\/strong>\uff0c\u518d\u5230**\u67b6\u6784\/\u4ea7\u54c1\u5b9a\u4e49\u8005\uff08Architect\/Product Thinker\uff09**\u7684\u8f6c\u53d8\u3002<\/p>\n\n\n\n

\u5f53\u524d\u7684AI\u6d6a\u6f6e\uff08\u5c24\u5176\u662f\u5927\u6a21\u578b LLM\uff09\u4e0e\u4f20\u7edf\u7684AI\u5f00\u53d1\uff08\u7eaf\u6570\u5b66\u548c\u6a21\u578b\u8bad\u7ec3\uff09\u4e0d\u540c\uff0c\u73b0\u5728\u7684\u95e8\u69db\u66f4\u591a\u5728\u4e8e**\u201c\u5982\u4f55\u7f16\u6392AI\u80fd\u529b\u6765\u89e3\u51b3\u95ee\u9898\u201d**\u3002<\/p>\n\n\n\n

\u4ee5\u4e0b\u662f\u6574\u7406\u597d\u7684\u5b66\u4e60\u8def\u7ebf\uff0c\u5206\u4e3a\u4e94\u4e2a\u9636\u6bb5\uff1a<\/p>\n\n\n\n

\n\n\n\n

\u7b2c\u4e00\u9636\u6bb5\uff1a\u8ba4\u77e5\u89c9\u9192\u4e0e\u6df1\u5ea6\u5e94\u7528\uff08\u6210\u4e3a AI Power User\uff09<\/h3>\n\n\n\n

\u5728\u8fd9\u4e2a\u9636\u6bb5\uff0c\u4f60\u7684\u76ee\u6807\u662f\u7406\u89e3 AI \u80fd\u505a\u4ec0\u4e48\uff0c\u4e0d\u80fd\u505a\u4ec0\u4e48\uff0c\u5e76\u5efa\u7acb\u201cAI\u601d\u7ef4\u201d\u3002<\/p>\n\n\n\n

    \n
  1. \u638c\u63e1\u4e3b\u6d41\u5de5\u5177\uff1a<\/strong>\u00a0\u6df1\u5165\u4f7f\u7528 ChatGPT (OpenAI), Claude (Anthropic), Midjourney (\u753b\u56fe), GitHub Copilot (\u7f16\u7a0b\u8f85\u52a9)\u3002\u5bf9\u6bd4\u5b83\u4eec\u7684\u4f18\u7f3a\u70b9\u3002<\/li>\n\n\n\n
  2. \u63d0\u793a\u8bcd\u5de5\u7a0b\uff08Prompt Engineering\uff09\uff1a<\/strong>\n
      \n
    • \u5b66\u4e60\u57fa\u672c\u6280\u5de7\uff1a\u89d2\u8272\u8bbe\u5b9a\u3001Few-Shot\uff08\u7ed9\u4f8b\u5b50\uff09\u3001Chain of Thought\uff08\u601d\u7ef4\u94fe\u63a8\u7406\uff09\u3002<\/li>\n\n\n\n
    • \u5b66\u4f1a\u7ed3\u6784\u5316\u63d0\u793a\u8bcd\uff1a\u4f7f\u7528\u7c7b\u4f3c XML \u6216 Markdown \u7684\u7ed3\u6784\u6765\u7f16\u5199\u590d\u6742\u7684\u6307\u4ee4\u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n
    • \u7406\u89e3\u57fa\u672c\u5c40\u9650\u6027\uff1a<\/strong>\u00a0\u4ec0\u4e48\u662f\u201c\u5e7b\u89c9\u201d\uff08Hallucination\uff09\uff1f\u4e3a\u4ec0\u4e48 AI \u4f1a\u4e00\u672c\u6b63\u7ecf\u5730\u80e1\u8bf4\u516b\u9053\uff1f\u4ec0\u4e48\u662f\u4e0a\u4e0b\u6587\u957f\u5ea6\uff08Context Window\uff09\u9650\u5236\uff1f<\/li>\n<\/ol>\n\n\n\n

      \u7b2c\u4e8c\u9636\u6bb5\uff1a\u6280\u672f\u539f\u7406\u626b\u76f2\uff08\u5efa\u7acb\u5e95\u5c42\u77e5\u8bc6\u4f53\u7cfb\uff09<\/h3>\n\n\n\n

      \u4e0d\u9700\u8981\u6210\u4e3a\u6570\u5b66\u5bb6\uff0c\u4f46\u5fc5\u987b\u7406\u89e3 AI \u8fd0\u8f6c\u7684\u903b\u8f91\uff0c\u5426\u5219\u4f60\u65e0\u6cd5\u8c03\u8bd5\u590d\u6742\u7684\u5e94\u7528\u3002<\/p>\n\n\n\n

        \n
      1. \u5927\u6a21\u578b\u539f\u7406\uff1a<\/strong>\u00a0\u4e86\u89e3 Transformer \u67b6\u6784\u662f\u4ec0\u4e48\uff08\u53ea\u9700\u8981\u77e5\u9053\u5b83\u662f\u901a\u8fc7\u201c\u5173\u6ce8\u201d\u4e0a\u4e0b\u6587\u6765\u9884\u6d4b\u4e0b\u4e00\u4e2a\u8bcd\uff09\u3002<\/li>\n\n\n\n
      2. \u6838\u5fc3\u672f\u8bed\uff1a<\/strong>\n
          \n
        • Token\uff1a<\/strong>\u00a0AI \u6d88\u8017\u7684\u6700\u5c0f\u5355\u4f4d\uff08\u8ba1\u8d39\u548c\u8ba1\u7b97\u7684\u57fa\u7840\uff09\u3002<\/li>\n\n\n\n
        • Embedding\uff08\u5411\u91cf\u5316\uff09\uff1a<\/strong>\u00a0\u5c06\u6587\u5b57\/\u56fe\u7247\u8f6c\u5316\u4e3a\u6570\u5b57\u6570\u7ec4\uff0c\u8fd9\u662f AI \u7406\u89e3\u4e16\u754c\u7684\u65b9\u5f0f\u3002<\/li>\n\n\n\n
        • Temperature\uff08\u968f\u673a\u6027\uff09\uff1a<\/strong>\u00a0\u63a7\u5236\u8f93\u51fa\u662f\u7a33\u5b9a\u8fd8\u662f\u521b\u610f\u7684\u53c2\u6570\u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n
        • \u591a\u6a21\u6001\uff1a<\/strong>\u00a0\u4e86\u89e3\u6587\u672c\u3001\u56fe\u7247\u3001\u58f0\u97f3\u662f\u5982\u4f55\u5728\u540c\u4e00\u4e2a\u6a21\u578b\u6216\u591a\u4e2a\u6a21\u578b\u95f4\u6d41\u8f6c\u7684\u3002<\/li>\n<\/ol>\n\n\n\n

          \u7b2c\u4e09\u9636\u6bb5\uff1aAI \u5f00\u53d1\u521d\u63a2\uff08API \u4e0e \u7f16\u6392\uff09<\/h3>\n\n\n\n

          \u8fd9\u662f\u4ece\u201c\u7528 AI\u201d\u5230\u201c\u505a AI \u5e94\u7528\u201d\u7684\u8de8\u8d8a\u3002<\/p>\n\n\n\n

            \n
          1. \u7f16\u7a0b\u57fa\u7840\uff1a<\/strong>\u00a0Python<\/strong>\u00a0\u662f AI \u9886\u57df\u7684\u552f\u4e00\u901a\u884c\u8bc1\uff0c\u5fc5\u987b\u719f\u7ec3\u638c\u63e1\u73af\u5883\u7ba1\u7406\uff08Conda\/Poetry\uff09\u548c\u57fa\u7840\u8bed\u6cd5\u3002<\/li>\n\n\n\n
          2. \u8c03\u7528 API\uff1a<\/strong>\u00a0\u5b66\u4e60\u5982\u4f55\u901a\u8fc7 Python \u8c03\u7528 OpenAI \u6216 Anthropic \u7684\u63a5\u53e3\uff0c\u5904\u7406\u6d41\u5f0f\u8f93\u51fa\uff08Streaming\uff09\u3002<\/li>\n\n\n\n
          3. LLM \u6846\u67b6\uff08\u91cd\u70b9\uff09\uff1a<\/strong>\n
              \n
            • LangChain \/ LangGraph\uff1a<\/strong>\u00a0\u76ee\u524d\u6700\u706b\u7684 AI \u7f16\u6392\u6846\u67b6\uff0c\u5b66\u4e60\u5982\u4f55\u628a\u591a\u4e2a AI \u6b65\u9aa4\u8fde\u6210\u201c\u94fe\u201d\u3002<\/li>\n\n\n\n
            • LlamaIndex\uff1a<\/strong>\u00a0\u4e13\u6ce8\u4e8e\u5904\u7406\u79c1\u6709\u6570\u636e\u7684\u6846\u67b6\u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n
            • \u4f4e\u4ee3\u7801\u5e73\u53f0\uff1a<\/strong>\u00a0\u5c1d\u8bd5\u00a0Dify<\/strong>\u00a0\u6216\u00a0Coze (\u6263\u5b50)<\/strong>\u3002\u8fd9\u4e9b\u5de5\u5177\u80fd\u8ba9\u4f60\u5feb\u901f\u7406\u89e3\u201c\u77e5\u8bc6\u5e93+\u5de5\u4f5c\u6d41+\u63d2\u4ef6\u201d\u7684\u6784\u5efa\u6a21\u5f0f\uff0c\u975e\u5e38\u9002\u5408\u5feb\u901f\u539f\u578b\u5f00\u53d1\u3002<\/li>\n<\/ol>\n\n\n\n

              \u7b2c\u56db\u9636\u6bb5\uff1a\u8fdb\u9636\u5f00\u53d1\uff08RAG \u4e0e Agent\uff09<\/h3>\n\n\n\n

              \u8fd9\u662f\u76ee\u524d\u4f01\u4e1a\u7ea7\u5e94\u7528\u6700\u6838\u5fc3\u7684\u4e24\u4e2a\u6280\u672f\u65b9\u5411\u3002<\/p>\n\n\n\n

                \n
              1. RAG (\u68c0\u7d22\u589e\u5f3a\u751f\u6210)\uff1a<\/strong>\n
                  \n
                • \u75db\u70b9\uff1a<\/strong>\u00a0\u89e3\u51b3 AI \u4e0d\u77e5\u9053\u4f60\u516c\u53f8\u79c1\u6709\u6587\u6863\u3001\u6570\u636e\u8fc7\u65f6\u7684\u95ee\u9898\u3002<\/li>\n\n\n\n
                • \u73af\u8282\uff1a<\/strong>\u00a0\u5b66\u4e60\u6587\u6863\u5207\u5206\uff08Chunking\uff09\u3001\u5411\u91cf\u6570\u636e\u5e93\uff08Vector DB, \u5982 Milvus, Pinecone, Chroma\uff09\u3001\u91cd\u6392\u5e8f\uff08Rerank\uff09\u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n
                • Agent (\u667a\u80fd\u4f53)\uff1a<\/strong>\n
                    \n
                  • \u5b66\u4e60\u5982\u4f55\u8ba9 AI \u81ea\u52a8\u4f7f\u7528\u5de5\u5177\uff08\u67e5\u8be2\u6570\u636e\u5e93\u3001\u641c\u7d22\u7f51\u9875\u3001\u53d1\u9001\u90ae\u4ef6\uff09\u3002<\/li>\n\n\n\n
                  • \u7406\u89e3\u201c\u89c4\u5212-\u8bb0\u5fc6-\u5de5\u5177\u4f7f\u7528\u201d\u7684 Agent \u95ed\u73af\u67b6\u6784\u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n
                  • \u672c\u5730\u90e8\u7f72\uff1a<\/strong>\u00a0\u5b66\u4e60\u4f7f\u7528\u00a0Ollama<\/strong>\u00a0\u6216\u00a0vLLM<\/strong>\u00a0\u5728\u672c\u5730\u8fd0\u884c\u5f00\u6e90\u6a21\u578b\uff08\u5982 Llama 3, DeepSeek\uff09\uff0c\u7406\u89e3\u63a8\u7406\u6210\u672c\uff08Inference Cost\uff09\u3002<\/li>\n<\/ol>\n\n\n\n

                    \u7b2c\u4e94\u9636\u6bb5\uff1a\u6a21\u578b\u8c03\u4f18\u4e0e\u5de5\u7a0b\u5316\uff08\u8d70\u5411\u8d44\u6df1\uff09<\/h3>\n\n\n\n
                      \n
                    1. \u5fae\u8c03 (Fine-tuning)\uff1a<\/strong>\u00a0\u4e86\u89e3\u4ec0\u4e48\u65f6\u5019\u9700\u8981\u5fae\u8c03\uff08\u6539\u53d8\u8bed\u6c14\u3001\u5b66\u4e60\u7279\u5b9a\u683c\u5f0f\uff09\uff0c\u4ec0\u4e48\u65f6\u5019\u4e0d\u9700\u8981\uff08\u901a\u5e38 RAG \u80fd\u89e3\u51b3 80% \u95ee\u9898\uff09\u3002\u4e86\u89e3 LoRA \u7b49\u8f7b\u91cf\u5316\u5fae\u8c03\u6280\u672f\u3002<\/li>\n\n\n\n
                    2. \u8bc4\u4f30 (Evaluation)\uff1a<\/strong>\u00a0AI \u8f93\u51fa\u5f88\u4e3b\u89c2\uff0c\u5b66\u4e60\u5982\u4f55\u7528\u7a0b\u5e8f\u8bc4\u4f30 AI \u7684\u56de\u7b54\u8d28\u91cf\uff08RAGAS \u6846\u67b6\u7b49\uff09\u3002<\/li>\n\n\n\n
                    3. AI \u8fd0\u7ef4 (LLMOps)\uff1a<\/strong>\u00a0\u76d1\u63a7 API \u6210\u672c\u3001\u5904\u7406\u8bf7\u6c42\u9650\u6d41\u3001\u63d0\u793a\u8bcd\u7248\u672c\u7ba1\u7406\u3002<\/li>\n<\/ol>\n\n\n\n
                      \n\n\n\n

                      \u5efa\u8bae\u7684\u5b66\u4e60\u8def\u5f84\u5efa\u8bae\uff08\u7531\u6d45\u5165\u6df1\uff09\uff1a<\/h3>\n\n\n\n
                        \n
                      • Week 1-2\uff1a<\/strong>\u00a0\u5237\u5b8c OpenAI \u5b98\u65b9\u7684\u300aPrompt Engineering for Developers\u300b\u514d\u8d39\u8bfe\u7a0b\uff08\u5434\u6069\u8fbe\u8054\u5408\u51fa\u54c1\uff09\u3002<\/li>\n\n\n\n
                      • Week 3-6\uff1a<\/strong>\u00a0\u52a8\u624b\u7528\u00a0Dify<\/strong>\u00a0\u642d\u5efa\u4e00\u4e2a\u57fa\u4e8e\u81ea\u5df1 PDF \u6587\u6863\u7684\u5bf9\u8bdd\u673a\u5668\u4eba\u3002<\/li>\n\n\n\n
                      • Week 7-10\uff1a<\/strong>\u00a0\u5b66\u4e60 Python\uff0c\u7ec3\u4e60\u7528 LangChain \u8c03\u7528 API \u5199\u4e00\u4e2a\u81ea\u52a8\u722c\u53d6\u65b0\u95fb\u5e76\u603b\u7ed3\u53d1\u9001\u90ae\u4ef6\u7684\u811a\u672c\u3002<\/li>\n\n\n\n
                      • \u957f\u671f\uff1a<\/strong>\u00a0\u5173\u6ce8 X (Twitter) \u4e0a\u7684 AI \u5927\u4f6c\u3001GitHub Trending \u699c\u5355\u4ee5\u53ca Hugging Face \u793e\u533a\u3002<\/li>\n<\/ul>\n\n\n\n

                        \u7ed9\u4f60\u7684\u907f\u5751\u6307\u5357\uff1a<\/h3>\n\n\n\n
                          \n
                        1. \u4e0d\u8981\u6c89\u8ff7\u4e8e\u63a8\u5bfc\u6570\u5b66\u516c\u5f0f\uff1a<\/strong>\u00a0\u9664\u975e\u4f60\u8981\u53bb\u5927\u5382\u641e\u5e95\u5c42\u7b97\u6cd5\u7814\u53d1\uff0c\u5426\u5219\u7406\u89e3\u903b\u8f91\u6bd4\u63a8\u5bfc\u516c\u5f0f\u91cd\u8981\u5f97\u591a\u3002<\/li>\n\n\n\n
                        2. \u591a\u52a8\u624b\uff0c\u5c11\u770b\u8bfe\uff1a<\/strong>\u00a0AI \u9886\u57df\u53d8\u5316\u6781\u5feb\uff0c\u770b\u53bb\u5e74\u7684\u89c6\u9891\u53ef\u80fd\u5df2\u7ecf\u8fc7\u65f6\u4e86\uff0c\u76f4\u63a5\u770b\u6700\u65b0\u6587\u6863\uff08\u5982 LangChain \u5b98\u7f51\uff09\u5e76\u8dd1\u901a Demo\u3002<\/li>\n\n\n\n
                        3. \u5173\u6ce8\u4e1a\u52a1\u903b\u8f91\uff1a<\/strong>\u00a0\u719f\u6089 AI \u7684\u5f00\u53d1\u8005\uff0c\u4ef7\u503c\u4e0d\u5728\u4e8e\u5199\u4ee3\u7801\uff0c\u800c\u5728\u4e8e**\u201c\u5982\u4f55\u628a\u4e1a\u52a1\u95ee\u9898\u62c6\u89e3\u6210 AI \u80fd\u5904\u7406\u7684\u6b65\u9aa4\u201d**\u3002<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

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