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Course Overview

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The Multivariate Analysis of Spectroscopic Data training is aimed at researchers and analysts who work with spectroscopic data, and are already familiar with fundamental multivariate methods such as PCA and PLS regression.

Who should participate in this program?

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The courses have been designed for individuals:

• Involved in R&D, product development, process optimization, quality control & monitoring
• Working with spectroscopic instruments (NIR, FTIR, UV, UV/VIS, NMR, DAS, Raman, Mass Spectroscopy) chromatography instruments (LC, GC, HPLC), production data, R&D, quality control or production processes

No prior knowledge of The Unscrambler® is required to attend our courses.

Course Details

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Day1

• Introduction to MVA application in spectroscopy
• Data import from various instruments and other sources
• Inspection of data (plotting, statistics, PCA)
• Identification of outliers in PCA
• Classification methods (SIMCA and discriminant analysis)

Day 2

• Pretreatment methods (derivation, scatter correction, SNV, etc)
• Calibration and prediction (PLSR)
• Model validation
• Outlier detection in PLS

Day 3

• Multivariate Curve Resolution (MCR)
• Advanced pretreatment (Extended scatter correction/EMSC)
• Exploration of student data sets

Instructor

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Ir. Gerben Mooiweer Statistical Expert, Douwe Egberts/R&D

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Gerben Mooiweer graduated from the Eindhoven University of Technology, Chemical Engineering and Chemistry department. He joined Douwe Egberts/R&D in 1977 as a technologist on coffee roasting, decaffeination, nut fryer temperature control, rice drying and various other projects focusing on mathematical modelling. In his current job he is a statistical expert for the Douwe Egberts R&D department. In this job he applies design of experiments, mathematical modelling and multivariate data analysis on a wide variety of data sources like sensory data, process data and metabolomics data using The Unscrambler® software. Beside his work at Douwe Egberts he is a guest lecturer at the TU Eindhoven teaching multivariate data analyses and MatLab courses.

General Terms

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The course fees includes lunch, tea / coffee, course material and 30-days trial installation of The Unscrambler. Participants are required to bring their own Laptop, organize transport to / from training venue and accommodation at their own cost. Deadline for registrations: 3 weeks before the course-start

Payments: 30 days net from date of invoice.
Cancellation: Cancellations up to 3 weeks prior the course start date, will be refunded with 50% of the registration fee, after this limit will not be refunded.
Substitution: The course participants may be substituted or join a later training provided that CAMO is notified.

Register