Course Overview
A practice-focused, free mini-course for engineers eager to integrate machine learning into real-world engineering projects.
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A practice-focused, free mini-course for engineers eager to integrate machine learning into real-world engineering projects.
Join Now For FreeMachine learning isn't only for computer scientists. This mini-course is crafted for engineers by engineers — focusing on industry-relevant ML skills you can apply immediately to your profession.
Looking to upskill and bring data-driven decision-making to your workplace.
Wanting to future-proof your career with a valuable, in-demand skill set.
Needing a practical understanding of ML for engineering project planning and innovation.
Anyone with an engineering mindset eager to master the basics of AI and ML.
Transform core engineering challenges into machine learning tasks and formulate solutions that impact your field.
Pick the right ML approach and implement hands-on models using Python and engineering datasets.
Explore techniques for preparing, cleaning, visualizing, and interpreting engineering data for ML insights.
Evaluate your models with metrics and validation approaches that matter to actual engineering performance.
Set the stage: Learn how machine learning fits within the engineering problem-solving toolkit.
Discover best practices for transforming raw data into powerful fuel for ML models.
Solve prediction tasks for continuous outcomes using hands-on regression algorithms.
Categorize engineering systems and results with key ML classification techniques.
Uncover hidden structure in your data with clustering and dimensionality reduction.
Measure and validate your models for reliable engineering application — not just academic success.
Integrate everything you've learned to solve an authentic engineering challenge using ML.