Wolfram U

Machine Learning & LLMs

Machine learning, neural networks and large language models (LLMs) are important components of modern AI systems. Learn about popular machine learning paradigms for classification, regression, clustering and anomaly detection with the help of fully automated and customizable functions that handle everything from feature extraction to performance evaluation. See how you can select pre-trained neural net models from a repository to apply to your own data, customize existing models or build models from scratch with the help of a symbolic neural net framework. Make use of Chat Notebooks as well as powerful built-in functions for calling LLM functionality and allowing LLMs to access Wolfram Language tools.

These courses cover many different topics, starting with introductory machine learning concepts and Wolfram Language built-in functions and diving into the complexities of building and training neural networks. Earn course completion certificates and prepare for Wolfram Language Level 1 certification.

Upcoming Events

  • MAR 12 | Online

    Turn Rough Ideas into Computation with Wolfram Notebook Assistant

    Learn how to turn conversational input into precise computational code for accessing the full power of Wolfram Language. This webinar demonstrates ways you can interact with Wolfram Notebook Assistant, showcases examples for writing and fixing code and explains how to take advantage of LLM functionality via Wolfram Language functions.

  • Mar 26 | Online

    Getting Started with AI: A Beginner's Guide to Automated Classification, Predictions and Computer Vision

    This webinar explains the basics of supervised and unsupervised machine learning in Wolfram Language using illustrative examples in a range of subjects.

  • APR 8–22 | 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.