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Provided by: Camo Process AS Multivariate Data Analysis Level 1 MVA 1 Process Analytical Technology PATAutomation |
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Training
Provided by Camo Process AS
The course is aimed at researchers, scientists and engineers
who work within life science and chemical industries. This course enables understanding of the central role of multivariate methods in Process Analytical Technology (PAT). Participants will learn how to interpret complex data quickly and confidently, and how to build robust models for process monitoring. Tailored to meet the needs of professionals and students, the course is designed around real-world applications, with intensive, hands-on training using The Unscrambler software.
Multivariate analysis tools helps process understanding and process improvement by interpreting complex data and presenting results in simple graphics and models.
Related Software Programs or Products: The Unscrambler (http://unscrambler.camo.com)
Related Awards, Degrees or Certifications: Certificate course on Multivariate Data Analysis Level 1 (MVA 1)Process Analytical Technology (PAT)
Related Jobs or Careers: - Professional engineers and managers involved in product manufacturing and development, Process Analytical Technology
(PAT)
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Multivariate Data Analysis Level 1 MVA 1 Process Analytical Technology PAT
Day 1
-Introduction to PAT
-Multivariate Analysis: General introduction and overview
-Overview of Quantification and prediction, Classification and
-Design of Experiments
-Raw Data and Data Imports
-Descriptive Statistics and exploratory data analysis: Check &
prepare and view your data
-Principles of projection methods: PCA
-Basic theory and result interpretation; Apply PCA for
exploratory data analysis, pattern recognition
-Outliers in PCA
-Overview of regression methods: PCA, MLR, PLS
Day 2
- Review of regression methods
- Calibration and prediction
- Demo regression
- Steps in multivariate regression
- Outliers in regression
- Spectroscopy and data preprocessing
- Smoothing and Derivative; Scatter Correction; Baseline
Correction; Center and Scale
- Validation and interpretation of PLS regression models
- Purpose and routine of cross-validation; Uncertainty test
- Prediction from PLS regression models
- Steps and rules in multivariate modeling
-Introduction to PAT
-Multivariate Analysis: General introduction and overview
-Overview of Quantification and prediction, Classification and
-Design of Experiments
-Raw Data and Data Imports
-Descriptive Statistics and exploratory data analysis: Check &
prepare and view your data
-Principles of projection methods: PCA
-Basic theory and result interpretation; Apply PCA for
exploratory data analysis, pattern recognition
-Outliers in PCA
-Overview of regression methods: PCA, MLR, PLS
Day 2
- Review of regression methods
- Calibration and prediction
- Demo regression
- Steps in multivariate regression
- Outliers in regression
- Spectroscopy and data preprocessing
- Smoothing and Derivative; Scatter Correction; Baseline
Correction; Center and Scale
- Validation and interpretation of PLS regression models
- Purpose and routine of cross-validation; Uncertainty test
- Prediction from PLS regression models
- Steps and rules in multivariate modeling
About The Training Provider: Camo Process AS
Camo Process AS - CAMO Software is a leading scientific and sensory software development company offering a complete range of multivariate data analysis solutions, which can be used to assist to implement a process of analytical technology (PAT) and quality by design (QbD) into their facilities.
We provide professional training on DoE (Design of Experiment), multivariate data analysis, spectroscopy,...
