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Description
The aim of the course is to provide all students with the necessary skill set to better leverage useful and actionable information from complicated bioprocessing data sets enabling improved data driven decisions to enhance bioprocessing performance.
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This course learning outcomes from this course are:
- Practical data analytic tools in Python
- Learn the basics of Python by analysing real-world data sets
- 听Create multivariate data analysis (MVDA) and machine learning (ML) models
- Evaluate and compare various models and identify the best model through analysis of the model performance metrics
- Build and validate advanced process models on challenging bioprocessing data sets
- Learn the optimum algorithms that are suitable for 鈥淏ig Data鈥� analytics through analysis of complex bioprocessing data sets
- Develop new algorithms that can automatically analyse large manufacturing data sets and compare model performance
- Leverage bioprocessing expertise and knowledge to help interpret results from data analysis to identify optimum process conditions
- Learn the most important statistics and data exploration tools necessary to make better processing decisions for challenging biomanufacturing data sets
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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