Eigenvector University Europe returns to Rome, Italy October 13-16, 2025 Complete Info Here!‎

Chemometrics and Machine Learning Summer School

July 29, 2025 - August 14, 2025


Eigenvector Research, Inc. is pleased to offer Chemometrics and Machine Learning Summer School, a live webinar-based short course covering basic and advanced machine learning methods with applications in chemometrics and chemical data science. The course will be delivered over three weeks with a specific focus each week.

Complete information about the course can be found by following the links below.

Target Audience

Chemometrics and Machine Learning Summer School is aimed at engineers, chemists and other scientists who want to be able to use pattern recognition and advanced data modeling methods to analyze complex data and develop their own models for calibration/regression or sample classification.

The course serves individuals with a need for exploratory data analysis, development of predictive models such as analytical instrument calibrations, soft sensor models, or sample classification. This is an introductory course, no prior knowledge is required though an understanding of basic statistics and linear algebra is helpful.

Course Description

This course will be delivered via webinar over three weeks, with three segments of three and a half hours each week, Tuesday-Wednesday-Thursday. The course material is drawn from our popular Eigenvector University series. The first week of the course, Basics and Pattern Recognition, will focus on the mathematical background required to understand chemometrics and machine learning methods and pattern recognition methods. This includes the most important data science method of all, Principal Components Analysis (PCA). Week two, Calibration Model Development, will concentrate on the development of linear regression models such as Partial Least Squares (PLS) and how they can be improved through preprocessing and variable selection. The third and final week, Classification and Non-linear Methods, will cover linear sample classification methods, then move onto non-linear methods for both classification and regression. This includes Artificial Neural Networks (ANN), Support Vector Machines (SVM) and others.

Emphasis will be on applying these techniques in the chemical process and laboratory environment for pattern recognition, instrument calibration, sample classification and exploratory data analysis. Many examples will be taken from spectroscopy (especially NIR and Raman) but other types of chemical data will be considered as well.

The courses will be delivered via Zoom. The sessions will be recorded and made available to the course participants. Students will be able to ask questions through the Zoom chat feature.

Software

The course will include many hands-on, follow-along examples. In order to take advantage of these, participants should equip their computers with current versions (9.5 or higher) of Solo or PLS_Toolbox (and MATLAB). Free demonstration copies of our software can be downloaded from your Eigenvector account for use during the course. If you don’t have an account, start by creating one. If you have not used our software before, we recommend that you download it and try it out before the course. We have many recorded webinars which will help you get started and show you how to use many popular chemometric and machine learning methods.

About the Instructors

The courses will be led by the Eigenvector Staff under the direction of Eigenvector President and PLS_Toolbox creator Barry M. Wise. Eigenvector Research has delivered hundreds of chemometrics courses at scientific conferences, on-site for companies, on-line and at our popular Eigenvector University each year in Seattle and at Eigenvector University Europe (this October in Rome).

Course Fee

Prices include instruction, course materials (provided in advance in .pdf format), access to the recorded version of the course, and a certificate of completion.

Prices shown are shown below. Payment must be received by 5pm PDT, Friday, July 25, 2025.

Chemometrics & Machine Learning Summer School
Regular
Academic
Price per week
$675
$225
All three weeks
$1800
$600

Note: Payment must be received by 5pm PDT, Friday, July 25, 2025. Credit card orders are strongly encouraged. Acceptable forms of payment include MasterCard, VISA, American Express, and checks drawn on a US bank. Wire transfers can also be arranged.

Academic discount: University students and faculty are eligible for the academic rate. Verification of University affiliation is required by providing valid university mailing and e-mail address. Note that we define academic as “degree granting institution.”

How to Register, Deadlines and Cancellations

To register, login to your Eigenvector account, or create an account, then select “Chemometrics and Machine Learning Summer School (online)” under the “Purchase” tab. You can then choose the specific weeks you would like to attend. You can pay directly with your MasterCard, VISA or American Express using our secure credit card processing. You may ask to be invoiced, however, payments must be received by 5pm PDT, Friday, July 25, 2025.

Complete refunds will be made for cancellations prior to July 18, 2025. No refunds will be made for cancellations after that date, however, substitutions are gladly accepted.

Schedule

Daily Schedule, Pacific Daylight Time (PDT)
06:45 – 07:00 Webex available for login
07:00 – 08:00 Instruction
08:00 – 08:10 Coffee Break
08:10 – 09:10 Instruction
09:10 – 09:20 Coffee Break
09:20 – 10:20 Instruction
10:20 – 10:30 Wrap-up and questions

Weekly Schedules and Course Outlines

Chemometrics and Machine Learning Summer School will presented over three weeks and will cover the following topics. Click on each course link for a complete description and outline.

Week 1, July 29-30-31, Basics and Pattern Recognition
Tuesday —  Linear Algebra for Machine Learning and Chemometrics, begin Chemometrics I: Principal Components Analysis
Wednesday — Chemometrics I: PCA, continued
Thursday — Complete Chemometrics I: PCA, cover elements of Data Visualization from Simple Plots to UMAP (t-SNE and UMAP, time permitting)

Week 2, August 5-6-7, Calibration Model Development
Tuesday —  Chemometrics II: Regression and Partial Least Squares
Wednesday — Complete Chemometrics II: PLS, begin Advanced Preprocessing for Spectral Applications
Thursday — Complete Advanced Preprocessing, cover elements of Variable Selection time permitting

Week 3, August 12-13-14, Classification and Non-linear Methods
Tuesday —  Clustering and Classification
Wednesday — Non-linear Machine Learning for Calibration and Classification
Thursday — Non-linear Machine Learning for Calibration and Classification continued