{"id":4860,"date":"2026-02-23T14:46:34","date_gmt":"2026-02-23T14:46:34","guid":{"rendered":"https:\/\/wolframu.wolfram.com\/?post_type=certifications&p=4860"},"modified":"2026-06-26T15:38:55","modified_gmt":"2026-06-26T15:38:55","slug":"level2-wolfram-tech-for-ai","status":"publish","type":"certifications","link":"https:\/\/www.wolfram.com\/wolfram-u\/certifications\/level2-wolfram-tech-for-ai\/","title":{"rendered":"Applied Expertise in Wolfram Technology for AI"},"content":{"rendered":"

Applied Expertise in Wolfram Technology for AI<\/h1>\r\n
Level 2 Certification<\/div>\r\n\r\n
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Wolfram U offers a growing suite of resources for learning how to integrate and complement modern AI systems with the precision of Wolfram Language computation. The Wolfram Technology for AI certification provides an opportunity to demonstrate that you can put this combination to work on a real problem. Earning this Level 2 certification requires submitting an independent project built entirely in a Wolfram Notebook that applies Wolfram LLM functions, computable data and computation tools together in a meaningful, original workflow. Submissions are assessed by the certification team according to a grading rubric covering technical correctness, integration depth, notebook clarity and the quality of the candidate's design judgment.
Learn more about the different levels of Wolfram certification<\/a><\/p>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n\r\n

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Level 2 Project<\/h2>\r\n

The Wolfram Technology for AI Level 2 certification is designed for developers, researchers and data practitioners who want to demonstrate that they can apply Wolfram LLM integration tools to solve a real, self-directed problem. Projects are built entirely as Wolfram Notebooks and must make meaningful use of one or more Wolfram LLM functions, such as LLMFunction, LLMSynthesize, LLMTool, LLMGraph, ChatObject, SemanticSearch or CreateVectorDatabase, while incorporating at least one element of the broader Wolfram technology stack, such as curated computable data, a Neural Net Repository model or a custom computation exposed as an LLMTool. The project should demonstrate that Wolfram computation and LLM reasoning are stronger together than either is alone.

\r\nThe following are representative examples of the kind of original, applied work suitable for Level 2 certification. Refer to the grading rubric for specific requirements related to LLM function coverage, integration depth, notebook structure and design documentation.<\/p>\r\n