NOTE: All seminars include all the material that the student might need: 

- Slides of the course (pdf).

- Exercises

- Datasets

- Toolboxes

- Refreshments during the lessons (coffee, tea, candies, cookies, and other amenities). This, of course, if we are allowed due to the Covid-19 pandemic situation

- We do NOT provide: Matlab and lunch

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SEMINAR 1 - PROGRAMMING

Introduction to Programming (Matlab, R and Python) for Multivariate Data Analysis

 

Since the very beginning, the ISC has always counted with a first week of Introduction to Matlab for Multivariate Data Analysis. It was a week that worked very well. We wanted to create something special. We have had many requests regarding Python and R. Therefore, we have decided to create a new module that includes the three major languages!

 

How does it work?

- Due to time constraints, The lessons will be online with pre-recorded videos.

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- The topics will be:

1) Language structure; 2) vectors and matrices; 3) arrays; 4) Basic operations; 5) Graphical Output, beginning; 6) Data structures and datasets; 7) Loops; 8) Conditions; 9) Another tricks in control flow; 10) Functions; 11) Data preprocessing; 12) Principal Component Analysis; 13) Graphical Output, advanced; 14) Images. We are planning between 4 - 6 hours of recordings per language.

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- They are three simultaneous courses. One per language, BUT:

1) The student will have access to ALL THE MATERIAL AND VIDEOS for the three courses. It is up to the student which language to follow.

2) ALL THE EXACT SAME MATERIAL (examples, exercises, etc) will be reproduced in the three languages.

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- The videos and material will be released on the 13th of May, 2024, and they will stay available until the end of 2024. Only the students who signed up officially will have access to the videos and material. It is REALLY ADVISABLE that the students run the material and practice during the week from the 13th of May until the 17th of May. During that period, we will create a consultancy platform where the teachers will be available to answer your questions and doubts.

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Dates and timetable: 13th - 17th of May 

 

Previous knowledge needed: None

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Software needed: Matlab, R, Python

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Teachers: José Manuel Amigo (Matlab), Sergey Kucheryavskyi (R), Anders Krogh Mortensen (Phyton).

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ECTS: 1

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Prices:

- University members: 600 DKK (The payment is made in Danish Krona - DKK - Approx. 81 euro / 98 USD)

- Industry/Private company: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 245 USD)

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SEMINAR 2 - BASIC

A basic introduction to Chemometrics, data types, data pre-processing, PCA, Multivariate Linear Regression, and Linear Algebra

 

This seminar contains two general topics:

 

- EXPLORE - Data exploration and regression: Principal Component Analysis has become the most powerful and versatile tool for exploring data tables in Analytical Sciences. Here we present a course to show the main benefits and drawbacks of PCA when it is used for different kinds of analytical data: Spectroscopy, environmental assessment, sensory, experiments performance, chromatography, etc. Moreover, preprocessing of different types of data will also be addressed in the seminar as a prerequisite for having the optimal possibility for exploring the data. If PCA is the keystone of pattern recognition methods, PLS is the keystone of multivariate calibration methods. This seminar will give a general overview of different multivariate calibration strategies (Multilinear Regression, Principal Component Regression), and will focus on Partial Least Squares regression.

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- LINAL - Linear Algebra: The Foundation for chemometric modeling is Linear Algebra. Why do the algorithms work? Why are the models meaningful? A math-derived answer to these questions can be found using linear algebra. The seminar will focus on hands-on experience with some fundamental linear algebra concepts, including rank, determinant, inverse, pseudo inverse, eigenvalues, singular value decomposition, orthogonality and basis sets. We will analyze a few real-life datasets, but the purpose of the seminar is to be a proficient mechanic unraveling the black box of algorithms and models, while other courses will learn you how to drive the car. 

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Dates and timetable: 20th of May - 24th of May. From 9 am until 4 pm (CET) with a 1-hour lunch break (30 hours)

 

Previous knowledge needed: None

 

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

- Matlab

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

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Teachers: José Manuel Amigo (EXPLORE) and Morten A. Rasmussen (LINAL).

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ECTS: 2.5

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Prices:

- University members: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 245 USD)

- Industry/Private company: 3750 DKK (The payment is made in Danish Krona - DKK - Approx. 505 euro / 612 USD)

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SEMINAR 3 - INTERMEDIATE

Intermediate topics on Chemometrics. Linear Classification, Variable selection methods, Multivariate Curve Resolution

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This seminar contains three general topics:

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- DoE - Design of Experiments: The course gives an introduction to the Design of Experiments. The course will highlight the critical points to address when designing our experiments. Some classical designs will be discussed (Full Factorial, Plackett-Burman, Central Composite) together with more advanced approaches like D-Optimal Designs.

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- VARSEL - Variable selection methods: In this one-day hands-on course on variable selection, you will become familiar with state-of-the-art variable selection. This will cover both classical, iterative, model-based and nature-inspired algorithms. I will also give you some pros and cons of the different methods, and some suggestions for how to operate them even better. The cases you will be working with can be done in R, Matlab (w/ wo PLS-toolbox) or python, all as you see fit. However, I only provide the necessary toolboxes for Matlab.

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- MCR - Multivariate Curve Resolution: The module will address the theoretical description and hands-on application of Multivariate Curve Resolution (MCR). MCR is a multivariate resolution (unmixing) method that can provide the description of a multicomponent data set through a bilinear model of chemically meaningful profiles, e.g., when analyzing an HPLC-DAD data set, MCR would provide the real elution profiles and the related UV spectra for each compound in the sample. It has applications in diverse fields, such as process analysis, chromatographic data, hyperspectral images or environmental data, in any context where a mixture analysis problem can be encountered. MCR can be applied to a single data matrix or to multiset structures formed by blocks of different information (data fusion). The module focuses mainly on the algorithm MCR-ALS (Multivariate Curve Resolution-Alternating Least Squares), and hands-on work will be done using a dedicated free GUI interface adapted to MATLAB environment. Applications will cover many of the areas mentioned above.

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Dates and timetable: 27th May - 31st of May. From 9 am until 4 pm (CET) with 1-hour lunch break (30 hours)

 

Previous knowledge needed: Basic multivariate data analysis and Matlab

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Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

- Matlab

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

- MCR-ALS toolbox: MCR-ALS toolbox can be freely downloaded here: https://mcrals.wordpress.com/download/mcr-als-2-0-toolbox/

- R Studio

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Teachers: Agnieszka Smolinska (DoE), Asmund Rinnan (VARSEL), Anna de Juan (MCR).

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ECTS: 2.5

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Prices:

- University members: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 245 USD)

- Industry/Private company: 3750 DKK (The payment is made in Danish Krona - DKK - Approx. 505 euro / 612 USD)

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CHALLENGES

This week is composed of different and individual seminars for a further understanding of more and extremely useful analytical methods. Some of them are on the same dates. So please, verify the dates to avoid overlapping.

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SEMINAR 4 - DL

Non-Linear Modeling and Deep Learning.

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This seminar aims at providing a basic introduction to the techniques which may be used in all those situations when a linear relation is not enough to provide accurate results (e.g. due to the presence of multiple sources of variability). In this respect, the most important aspects of data modeling will be considered (exploratory analysis, classification and calibration). Topics such as kernel and dissimilarity-based approaches (including support vector machines), local modeling (kNN and locally weighted regression/classification), and different artificial neural network architectures (shallow learning and deep learning) will be covered. 

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Dates and timetable: 3rd of June - 5th of June. From 9 am until 4 pm (CET) with 1-hour lunch break (30 hours)

 

Previous knowledge needed: Basic multivariate data analysis

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Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

- Matlab and Python

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

- Deep Learning Toolbox of Matlab

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Teacher: Jesper Løve Hinrich (20th and 21st of June).

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ECTS: 1.5

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Prices:

- University members: 900 DKK (The payment is made in Danish Krona - DKK - Approx. 120 euro / 120 USD)

- Industry/Private company: 2250 DKK (The payment is made in Danish Krona - DKK - Approx. 300 euro / 300 USD)

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SEMINAR 5 - CLASS

Linear and nonlinear Classification​

 

The course will deal with the main linear classification methods like Discriminant Analysis, Partial Least Squares Discriminant Analysis (PLS-DA) and SIMCA. We will see both theoretical aspects and practical applications. The last two days will focus on more complex models like Support Vectors Machine, Random Forests and Self-Organized Maps Artificial Neural Networks. The seminar consists of theoretical sessions together with a collection of exercises designed to understand the fundamentals of the three abovementioned methods.

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Dates and timetable: 3th of June - 6th of June. From 9 am until 4 pm (CET) with 1-hour lunch break (12 hours)

 

Previous knowledge needed: Basic multivariate data analysis.

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Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

- Matlab

- The Classification toolbox can be freely downloaded from here: https://michem.unimib.it/download/matlab-toolboxes/classification-toolbox-for-matlab/

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Teacher: Davide Ballabio

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ECTS: 2

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Prices:

- University members: 1200 DKK (The payment is made in Danish Krona - DKK - Approx. 162 euro / 162 USD)

- Industry/Private company: 3000 DKK (The payment is made in Danish Krona - DKK - Approx. 400 euro / 400 USD)

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SEMINAR 6 - DF

Data Fusion

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The seminar will deal with the chemometric approaches for integrating (“fusing”) data from different sources. First of all, the various configurations which may occur when dealing with multiple data matrices will be presented and discussed, and a hierarchy/systematization of the possible data fusion approaches will be introduced. Then the main multi-block strategies for data exploration and predictive modeling will be discussed and compared, and further classification of models depending on whether the globally common, locally common and distinct information is considered or not will be introduced. The theoretical and algorithmic description of the methods will be accompanied by worked examples of real data sets.

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Dates and timetable: 5th - 6th of June. From 9 am until 4 pm (CET) with 1-hour lunch break (12 hours)

 

Previous knowledge needed: Basic multivariate data analysis

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Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

- Matlab

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Teacher: Federico Marini

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ECTS: 1

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Prices:

- University members: 600 DKK (The payment is made in Danish Krona - DKK - Approx. 81 euro / 81 USD)

- Industry/Private company: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 200 USD)

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SEMINAR 7 - MW

Multi Way analysis

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Multi-way data is gaining popularity due to the capability of scientific devices to generate data with, at least, 3 dimensions (elution time – mz channel – samples, excitation-emission – sample, etc). Therefore, learning the basics of multi-way analysis will help to extract the most of that complex data structure. In this sense, methods like parallel factor analysis (PARAFAC) and PARAFAC2 will be studied and applied to different examples.

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Dates and timetable: 22nd of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (6 hours)

 

Previous knowledge needed: Basic multivariate data analysis

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Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

- Matlab

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

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Teacher: Beatriz Quintanillas

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ECTS: 0.5

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Prices:

- University members: 300 DKK (The payment is made in Danish Krona - DKK - Approx. 40 euro / 40 USD)

- Industry/Private company: 750 DKK (The payment is made in Danish Krona - DKK - Approx. 100 euro / 100 USD)

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SEMINAR 8 - GLUE (How not to make Chemometrics) and WORKSHOP

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This seminar is divided into two parts:

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- Morning: 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.

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- Afternoon: 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.

 

Dates and timetable: 7th of June. From 9 am until 4 pm (CET) with 1-hour lunch break (6 hours)

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Previous knowledge needed: Chemometrics

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Software: Up to you!

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Teacher: José Manuel Amigo, Rasmus Bro, Federico Marini and Davide Ballabio

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ECTS: 0

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Price: 0 DKK (Approx. 0 euro / 0 USD)

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