Seminars: 
This is a brief description of the seminars at ISC-2023. For further details, see below

1 - PROGRAMMING - Introduction to Programming for Multivariate data analysis in Matlab, Python and R 
This online seminar is based on online pre-recorded videos that are thought to be an introduction to the main aspects of dealing with Matlab, R and Python focused on Multivariate Data Analysis.

2 - BASIC - Basic Introduction to Chemometrics and Linear Algebra
This seminar includes two parts. EXPLORE and LINAL. A basic introduction to Chemometrics. Data types, PCA, pre-processing, Multivariate Regression, and Linear Algebra focused on Chemometrics.

3 - INTERMEDIATE:
This seminar includes three parts. CLASS, Multivariate Classification; VARSEL, variable selection methods; MCR, Multivariate Curve Resolution.

4 - DL - Non-Linear Modeling / Deep Learning
This seminar includes two parts. Methods for Non-linear modeling and the different architectures of Artificial Neural Networks (basic structures, shallow neural networks and deep neural networks.

5 - DoE - Design of Experiments 
Design of Experiments is an essential part of sciences that helps the optimization of processes, the study of experimental domains and, consequently, gaining in knowledge. This seminar will explore the main experimental designs used in sciences.

6 - ASCA - ANOVA Simultaneous Component Analysis 
Based on ANOVA variance partitioning followed by bi-linear modeling of the individual effect matrices, the method offers detailed insight into small systematic variance contributors that otherwise are masked and uncovered by traditional techniques such as PCA.

7 - MW - Multiway Data Analysis
Methods like parallel factor analysis (PARAFAC) and PARAFAC2 will be studied and applied to different examples.-Simultaneous Component Analysis.

8 - DF - Data Fusion
The seminar will deal with the chemometric approaches for integrating (“fusing”) data from different sources. We will learn the different strategies for fusing data, analyzing it, and interpreting the results.

9 - GLUE (How not to make Chemometrics) and WORKSHOP
We will take a very close look at all the most common mistakes that even experienced people will do when doing multivariate analysis. We will cover exploration, calibration, interpretation, visualization and many other subjects. And always with a focus on what is the most common problem as well as a sounder alternative. 

​Workshop: Any student of the School will be able to ask whatever question remaining from any seminar. Also, there will be time to work on your own data and check with us on the analysis workflow.