Workshops / Trainings
Workshops / Trainings
1 Day Workshop / Training

Industrial Perspectives in Analytical Methods



For Registration:

Dr.T.SUDHAMANI  -  +91 9842457080

(OR)
Please email your contact details to
Industrial Perspectives in Analytical Methods and Training on Chemometrics Software

The purpose of workshop is to provide students with an opportunity for an in-depth discussion on a specific topic important to pharmaceutical analysis in general. It also helps to concentrate on emerging research and current trends applied in the field of analytical techniques. This workshop focuses on bridging the gap between the industry and academics and it also gives an idea about what is expected from the academicians by the industry.

Chemometrics means performing calculations on measurements of chemical data. The common usage of the word refers to using linear algebra calculation methods to make either quantitative or qualitative measurements of chemical data and primarily spectra. The software is used in a range of industries and research for Exploratory Data Analysis, Descriptive Statistics, Regression Analysis, Classification & Prediction and Design of Experiments.

The topics will be delivered by recognized experts who are well versed in the latest developments of analytical field. The workshop will provide updated information on key issues that are concerned with Chemometrics to participants. The delegates will get “UNSCRAMBLER X” software on Chemometrics installed in their laptop for 30 days free. The workshop will have presentations and demonstrations on Chemometrics software.

Audience and language
This course is intended for students, specialists, and scientists with an interest in exploring recent advancements in spectroscopy and Chemometrics. No previous experience with statistical software or chemometrics is also expected. The course language will be English

Terminologies:

Analytical Instruments, Spectrophotometers, NIR, FT-NIR, Raman, GCMS, NMR, HyperSpectral Imaging, multispectral Imaging, Statistical Data Analysis, Chemometrics, Multivariate Data Analysis (MVA), Principal Component Analysis (PCA), Partial Least Square Regression (PLS), PLS Discriminate Analysis (PLS-DA), Quality by Design (QbD), Design of Experiments (DOE), Multivariate Statistical Process Controls (MSPC), Image Analysis, Microscopic Image Analysis, STM, AFM, Peak Analysis, Curve Fitting, Process Monitoring, Factor Analysis, Analysis of Variance (ANOVA), Response Surface Analysis (RSM), Machine Learning(ML), Early Events Detection(EED), Artificial Intelligence(AI), etc…