By Scientists for scientists

Machine Learning for Scientists & Engineers

Machine Learning for Scientists & Engineers

Track Machine Learning Track, Managerial Track

Acquire skills in the basics of machine learning using problems drawn from science and engineering data sets. The course focuses primarily on supervised learning, regression, classification, and unsupervised machine learning strategies.

Course Hours20 hours

Course Overview

Machine Learning for Scientists and Engineers provides scientists and engineers with a practical introduction to classical machine learning using Scikit-learn.

The course focuses primarily on supervised learning, starting with regression and then moving into Classification.

Some unsupervised machine learning strategies will also be covered.

This course builds a solid foundation of the basics of machine learning, using problems drawn from science and engineering data sets.

Prerequisite

This course requires basic proficiency with Python and the scientific Python stack. Some practical experience with Jupyter Notebooks, NumPy (ndarrays), Pandas (DataFrames), and scientific visualization in Python using Matplotlib are essential to working with the code and concepts presented in this course.

If you have taken Enthought’s Python Foundations for

Scientists and Engineers, you have the requisite background knowledge for this course.

Lectures

Introduction to AI/MLBasic Terminology, Models
Introduction to scikit-learn API, ML Workflow
RegressionRegression Models, Scoring
Feature Engineering I Univariate & Bivariate Analysis
Feature Engineering IIMultivariate & Interaction Analysis
Feature Selection & TuningRegularization, Hyperparameters
Model Selection – GLM, SVM, Decision Trees, Ensemble
Classification I – Classification Models, Scoring
Classification II – Classification Workflow
Clustering – Algorithms

Instructors

Enthought instructors have advanced degrees in scientific fields such as physics, engineering, computer science, and mathematics, and all have extensive experience through research and consulting in applying Python to solve complex problems across a range of industries, allowing them to bring their real world experience to the classroom every day.

Packages

scikit-learn, seaborn

Interested in corporate training?

For more information, contact the Enthought Academy team.

Our Scientific Python Experts

Enthought Academy instructors are scientists and engineers themselves and have deep knowledge and understanding of the strategies and technologies covered in each track, and extensive practical experience applying Python to solve complex challenges across a range of science-based industries.

Alexandre Chabot-Leclerc

Vice President, Digital Transformation Solutions

Tim Diller

Director, Digital Transformation Services

Mark Dickinson

Director, Software Architecture

Eric Olsen

Director, Training Solutions

Glen Granzow

Scientific Software Technical Trainer

Sogo Shiozawa

Scientific Software Developer

Kuya Takami

Senior DTX Services Consultant and Instructor

Logan Thomas

Senior DTX Services Consultant and Instructor