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The course will provide an introduction into the most important statistics and data exploration tools necessary to evaluate challenging bioprocess data sets. In addition, support the user to navigate which MVDA or ML algorithm should be implemented to better understand the cause and effect relationships within their data and how to apply these tools to generate predictions of key process parameters.
This course will provide the delegate with the following skillset:
- Practical data analytic tools in Python: Learn the basics of Python by analysing real-world data sets
- Multivariate data analysis (MVDA) and Machine learning (ML) expertise: Build and validate advanced process models on challenging bioprocessing data sets
- “Big Data” analytics: How to deal with large manufacturing data sets and automate the model building process
- Bioprocessing expertise and knowledge: Learn the most important statistics and data exploration tools necessary to interpret challenging biologic data sets
- The aim of the course is provide all attendees with the necessary skill set to better leverage useful and actionable information from complicated bioprocessing data sets.
The course will utilise a wide range of real-life industrial data sets collected from both upstream and downstream operations and will demonstrate all the necessary data importation, pre-processing, visualization and analysis steps to better inform bioprocess monitoring and control operations.
The cost of the course includes tuition, course materials, lunches, refreshments and a networking dinner. Accommodation is not included.
