Machine Learning for Engineers 2022 | Engineering, Data Science

Gain practical experience in applying machine learning techniques to solve real-world engineering problems with this comprehensive course covering theory, applications, and hands-on projects.

Introduction

Machine learning adapts using data to gain experience. It is a convergence of linear algebra, statistics, optimization, and computational methods for computer systems to infer relationships and make decisions from data. This engineering course reviews theory and applications of machine learning to engineering applications with a survey of unsupervised and supervised learning methods.

Highlights

• Combines mathematical details with several case studies that provide an intuition for machine learning with methods for classification, regression, and dimensionality reduction
• Hands-on group project to build working fluency in state-of-the-art methods implemented in MATLAB and Python
• Covers engineering-specific programming, cybersecurity, data science, data visualization, and high-performance computing

Recommendation

This course is recommended for engineers looking to gain practical experience in applying machine learning techniques to solve real-world engineering problems. The course provides a strong foundation in the theory and applications of machine learning, as well as hands-on experience with industry-standard tools and technologies.