Introduction to Machine Learning in Wolfram Language
- Instructor Led
- 2 h 30 min
- Beginner
- 1 Certification
Estimated Time: 2 h 30 min
Course Level: Beginner
Requirements: This course requires basic working knowledge of Wolfram Language.
Certification Levels: Completion

This course introduces the easy-to-use machine learning superfunctions available in Wolfram Language. You will learn how to perform supervised and unsupervised learning tasks with just a few lines of code. We will start with regression, classification, clustering and anomaly detection, and from there, we'll move on to the state-of-the-art neural net framework. Examples using the Wolfram Neural Net Repository are shown with instructions for building your own neural networks from scratch. Basic familiarity with Wolfram Language or introductory-level skill in any programming language is recommended.
Featured Products & Technologies: Mathematica, Wolfram Language
Outline
- Introduction to Machine Learning
- Supervised Learning
- Unsupervised Learning
- The Neural Network Framework
Schedule
- Register Now
Thursday, October 19
12–2:30pm CDT, 5–7:30pm GMT| Online | FreeYour local time - Register Now
(Korean)
Thursday, November 2310am–5pm KST | Seoul, South Korea | ₩495,000
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Certifications Available
Completion Certificate
Certify your completion of this course by attending an online class and passing the quiz.