Artificial Intelligence

From classical machine learning to the frontiers of symbolic computation and the latest LLM technology, Wolfram Language provides a unique, integrated environment for artificial intelligence (AI) research, education and deployment. Wolfram U courses provide instruction in foundational AI technologies, tools and concepts, including machine learning, neural networks, natural language processing, computer vision and more. Learn to use Wolfram AI Assistant and explore how to build, customize and deploy AI solutions using Wolfram technologies.

These courses cover topics from introductory explanations to generative AI capabilities and advanced AI applications across text, images, audio and data analysis. Earn course completion certificates and Wolfram Level 1 proficiency certifications and develop an independent project for Level 2 certification for Applied Expertise in Wolfram Technology for AI.

Upcoming Events

  • SEP 8 | Online

    Wolfram MCP: Connecting AI Coding Tools to Wolfram Language

    Large language models can write code but can't actually compute; this livestream shows how the Wolfram MCP server closes that gap. By giving AI tools direct access to a Wolfram Language kernel, Wolfram MCP lets your assistant evaluate code, work directly with notebooks and draw on real computation and curated data in Wolfram Language development, data analysis and research workflows.

  • SEP 14–18 | Online

    Daily Study Group: Integrating AI for Chemistry Problem Solving

    Join this Daily Study Group to explore how modern AI tools can enhance productivity in chemistry research and education. Learn to leverage the built-in Wolfram AI Assistant alongside Wolfram Language LLM functions and the integrated Wolfram Knowledgebase for chemistry data.

  • Oct 6–20 | Online

    Exploring AI Foundations with Wolfram Tools

    This three-part course sequence guides you in using the computational power of Wolfram technologies as a foundation for reliable AI systems. Discover concepts in machine learning, explore the Neural Net Repository and learn to use LLMs.