new doc

digoal · digoal · commit 474c33bb6659 · 2025-04-26T16:15:41.000+08:00
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 digoal                  
                   
 ### 日期                  
-2025-04-25                 
+2025-04-26                 
                   
 ### 标签                  
 PostgreSQL , PolarDB , DuckDB , RAG , 佐证 , AI , 大模型 , 胡编乱造 , 证明 , 证伪    
diff --git a/202504/20250426_06.md b/202504/20250426_06.md
@@ -0,0 +1,202 @@
+## 裸考拿下Oracle AI Foundations Associate认证    
+                      
+### 作者                      
+digoal                      
+                      
+### 日期                      
+2025-04-26                     
+                      
+### 标签                      
+PostgreSQL , PolarDB , DuckDB , Oracle AI 认证     
+                      
+----                      
+                      
+## 背景       
+和MySQL免费认证一个尿性: [《德说-第327期, MySQL认证免费了, 它的“阴谋”是什么?》](../202504/20250425_04.md)      
+    
+Oracle AI 认证也免费了, 考完告诉大家一下, 里面其实很多都是暗藏宣传自家OCI的内容, 自行甄别吧.      
+    
+有了阿里云大模型(LLM) ACA ACP的认证基础, 考Oracle AI Foundations Associate认证非常轻松. 40道题60分钟, 裸考居然98分通过.      
+  
+![pic](20250426_06_pic_002.jpg)  
+  
+![pic](20250426_06_pic_001.jpg)  
+    
+下面是阿里云 [《大模型(LLM) ACA ACP 通关经验分享》](../202504/20250411_01.md)  . ACA ACP考试辅导资料非常有价值, 建议学习.      
+    
+Oracle AI 认证在Oracle Cloud Infrastructure (OCI) 体系里     
+- https://www.oracle.com/cn/education/certification/#oci     
+    
+搜索Oracle AI相关的认证    
+- https://mylearn.oracle.com/ou/search/oracle-ai-vector-search-professional    
+    
+发现有3个AI相关的认证, 其中第一个是免费考的, 地址也有点不太一样exam-unproctored下.      
+    
+学习视频都免费, 就算不考也可以学习一下, 学到就是自己的.    
+    
+    
+### 1、Oracle Cloud Infrastructure 2025 AI Foundations Associate    
+    
+免费课程:    
+    
+https://mylearn.oracle.com/ou/course/oracle-cloud-infrastructure-ai-foundations/147805/223411    
+    
+免费考试地址:    
+    
+https://mylearn.oracle.com/ou/exam-unproctored/oracle-cloud-infrastructure-2025-ai-foundations-associate-1z0-1122-25/147781/241962    
+    
+### 2、Oracle Cloud Infrastructure 2025 Generative AI Professional    
+    
+免费课程:    
+    
+https://mylearn.oracle.com/ou/learning-path/become-a-oci-generative-ai-professional/147863    
+    
+https://mylearn.oracle.com/ou/course/oracle-cloud-infrastructure-generative-ai-professional/147932/243479    
+    
+付费考试地址:    
+    
+https://mylearn.oracle.com/ou/exam/oracle-cloud-infrastructure-2025-generative-ai-professional-1z0-1127-25/35644/147386/241953    
+    
+https://education.oracle.com/products/trackp_OCI25GAIOCP    
+    
+`¥1,671`    
+```    
+Format: Multiple Choice    
+Duration: 90 Minutes    
+Exam Price: ¥1,671    
+Number of Questions: 50    
+Passing Score: 68%    
+Validation: This exam has been validated against Oracle Cloud Infrastructure 2025    
+Policy: Cloud Recertification    
+```    
+    
+考点    
+    
+Objectives	| % of Exam    
+---|---    
+ Fundamentals of Large Language Models (LLMs)	|20%    
+ Using OCI Generative AI Service	|40%    
+ Implement RAG using OCI Generative AI service	|20%    
+ Using OCI Generative AI RAG Agents service |	20%    
+     
+    
+Fundamentals of Large Language Models (LLMs)    
+- Explain the fundamentals of LLMs    
+- Understand LLM architectures    
+- Design and use prompts for LLMs    
+- Understand LLM fine-tuning    
+- Understand the fundamentals of code models, multi-modal, and language agents    
+    
+Using OCI Generative AI Service    
+- Explain the fundamentals of OCI Generative AI service    
+- Use pretranined foundational models for Chat and Embedding    
+- Create dedicated AI clusters for fine-tuning and inference    
+- Fine-tune base models with custom dataset    
+- Create and use model endpoints for inference    
+- Explore OCI Generative AI security architecture    
+    
+Implement RAG using OCI Generative AI service    
+- Explain OCI Generative AI integration with LangChain and Oracle Database 23ai    
+- Explain RAG and RAG workflow    
+- Discuss loading, splitting and chunking of documents for RAG    
+- Create embeddings of chunks using OCI Generative AI service    
+- Store and index embedded chunks in Oracle Database 23ai    
+- Describe similarity search and retrieve chunks from Oracle Database 23ai    
+- Explain response generation using OCI Generative AI service    
+    
+Using OCI Generative AI RAG Agents service    
+- Explain the fundamentals of OCI Generative AI Agents service    
+- Discuss options for creating knowledge bases    
+- Create and deploy agents using knowledge bases     
+- Invoke deployed RAG agent as a chatbot     
+    
+    
+    
+### 3、Oracle AI Vector Search Professional    
+免费课程:    
+    
+https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-fundamentals/140188/223444    
+    
+付费考试地址:    
+    
+https://mylearn.oracle.com/ou/exam/oracle-ai-vector-search-professional-1z0-184-25/35644/144913/236030    
+    
+https://education.oracle.com/ouexam-pexam_1z0-184-25/pexam_1Z0-184-25    
+    
+    
+`¥1,671`    
+Format: Multiple Choice    
+Duration: 90 Minutes    
+Exam Price: ¥1,671    
+Number of Questions: 50    
+Passing Score: 68%    
+Validation: This exam is valid for Oracle Database 23ai    
+    
+    
+    
+考点:    
+    
+The following table lists the exam objectives and their weightings.    
+    
+Objectives	| % of Exam    
+---|---    
+ Understand Vector Fundamentals	|20%    
+ Using Vector Indexes	|15%    
+ Performing Similarity Search	|15%    
+ Using Vector Embeddings	|15%    
+ Building a RAG Application	|25%    
+ Leveraging related AI capabilities	|10%    
+    
+Understand Vector Fundamentals            
+- Use Vector Data type for storing embeddings and enabling semantic queries    
+- Use Vector Distance Functions and Metrics for AI vector search    
+- Perform DML Operations on Vectors    
+- Perform DDL Operations on Vectors    
+    
+Using Vector Indexes            
+- Create Vector Indexes to speed up AI vector search    
+- Use HNSW Vector Index for search queries     
+- Use IVF Vector Index for search queries    
+    
+Performing Similarity Search            
+- Perform Exact Similarity Search    
+- Perform approximate similarity search using Vector Indexes    
+- Perform Multi-Vector similarity search for multi-document search    
+    
+Using Vector Embeddings            
+- Generate Vector Embeddings outside the Oracle database    
+- Generate Vector Embeddings inside the Oracle database    
+- Store Vector Embeddings in Oracle database    
+    
+Building a RAG Application            
+- Understand Retrieval-augmented generation (RAG) concepts    
+- Create a RAG application using PL/SQL    
+- Create a RAG application using Python    
+    
+Leveraging related AI capabilities            
+- Use Exadata AI Storage to accelerate AI vector search    
+- Use Select AI with Autonomous to query data using natural language prompts    
+- Use SQL Loader for loading vector data    
+- Use Oracle Data Pump for loading and unloading vector data    
+    
+  
+#### [期望 PostgreSQL|开源PolarDB 增加什么功能?](https://github.com/digoal/blog/issues/76 "269ac3d1c492e938c0191101c7238216")
+  
+  
+#### [PolarDB 开源数据库](https://openpolardb.com/home "57258f76c37864c6e6d23383d05714ea")
+  
+  
+#### [PolarDB 学习图谱](https://www.aliyun.com/database/openpolardb/activity "8642f60e04ed0c814bf9cb9677976bd4")
+  
+  
+#### [PostgreSQL 解决方案集合](../201706/20170601_02.md "40cff096e9ed7122c512b35d8561d9c8")
+  
+  
+#### [德哥 / digoal's Github - 公益是一辈子的事.](https://github.com/digoal/blog/blob/master/README.md "22709685feb7cab07d30f30387f0a9ae")
+  
+  
+#### [About 德哥](https://github.com/digoal/blog/blob/master/me/readme.md "a37735981e7704886ffd590565582dd0")
+  
+  
+![digoal's wechat](../pic/digoal_weixin.jpg "f7ad92eeba24523fd47a6e1a0e691b59")
+  
diff --git a/202504/20250426_06_pic_001.jpg b/202504/20250426_06_pic_001.jpg
diff --git a/202504/20250426_06_pic_002.jpg b/202504/20250426_06_pic_002.jpg
diff --git a/202504/readme.md b/202504/readme.md
@@ -2,6 +2,7 @@
   
 ### 文章列表  
 ----  
+##### 20250426_06.md   [《裸考拿下Oracle AI Foundations Associate认证》](20250426_06.md)  
 ##### 20250426_05.md   [《德说-第329期, RAG逆向应用 | 谷歌Gemini实现AI回复结果核查(证明或证伪)功能》](20250426_05.md)  
 ##### 20250426_04.md   [《AI论文解读 | BM25 Query Augmentation Learned End-to-End》](20250426_04.md)  
 ##### 20250426_03.md   [《AI论文解读 | Injecting the BM25 Score as Text Improves BERT-Based Re-rankers》](20250426_03.md)  
diff --git a/README.md b/README.md
@@ -100,6 +100,7 @@ digoal's|PostgreSQL|文章|归类
   
 ### 六、所有文档如下  
 ----  
+##### 202504/20250426_06.md   [《裸考拿下Oracle AI Foundations Associate认证》](202504/20250426_06.md)  
 ##### 202504/20250426_05.md   [《德说-第329期, RAG逆向应用 | 谷歌Gemini实现AI回复结果核查(证明或证伪)功能》](202504/20250426_05.md)  
 ##### 202504/20250426_04.md   [《AI论文解读 | BM25 Query Augmentation Learned End-to-End》](202504/20250426_04.md)  
 ##### 202504/20250426_03.md   [《AI论文解读 | Injecting the BM25 Score as Text Improves BERT-Based Re-rankers》](202504/20250426_03.md)  
