ML/AI Datasets using PyMAPDL

With the introduction of PyAnsys technology, the scope of engineering simulations has rapidly expanded. This Ansys Innovation Course explores how PyMAPDL serves as a robust tool for developing physics-based numerically accurate, synthetic datasets for the applications relying on Machine Learning and Artificial Intelligence. A foundational understanding of Python and APDL scripting is assumed for this course, so if you're unfamiliar with these topics, we recommend reviewing our courses on “Intro to Python”, “Intro to Ansys APDL Scripting”, and "Getting Started with PyMAPDL" beforehand.

A course completion badge allows you to showcase your success. We partner with the Credly Acclaim platform, and digital badges can be used in email signatures, digital resumes and social media sites. The digital image contains verified metadata that describes your participation in our course and the topics and skills that were covered. This badge is for successfully completing the Material Selection and Eco-Analysis for ChassisML/AI Datasets using PyMAPDL course.

Disclaimer: The PyMAPDL scripts are based on version 0.68.1 of PyMAPDL. Please see the latest PyMAPDL documentation for any discrepancies.
This course focuses on the core concepts and the functionalities of PyMAPDL and its application for generating synthetic datasets. It does not cover the generation and/or implementation of Machine Learning algorithms. If you are looking for information on the same, we recommend seeking additional resources or courses specific to that topic.

Links for the recommended courses for Python and APDL - 

Intro to Python - ANSYS Innovation Courses

Intro to Ansys APDL Scripting in Mechanical - ANSYS Innovation Courses

Getting Started with PyMAPDL - ANSYS Innovation Courses

Alternate video link.