Data Analytics and Machine Learning with Python

Data Analytics and Machine Learning with Python: Foundations and Applications in Bioprocessing is a 5-day instructor-led program designed for beginners eager to break into data analytics and AI. Tailored for life sciences and bioprocessing professionals, this course bridges the gap between technical data science skills and real-world bioprocess applications.

You’ll begin with the fundamentals of Python programming—variables, functions, control structures, and libraries like NumPy and Pandas. The course then guides you through data wrangling and exploratory data analysis (EDA), using visualization tools such as Matplotlib and Seaborn to uncover insights from raw datasets.

The program moves into machine learning, covering both supervised techniques (e.g., regression and classification) and unsupervised learning (e.g., clustering and dimensionality reduction). You’ll learn how to build and evaluate predictive models for real bioprocess problems, such as monitoring and control.

In the final stage, the course explores the role of AI in process design, optimization, and scale-up, equipping participants with tools to analyze large-scale data and automate decision-making in complex environments. A capstone project gives learners the chance to apply all concepts to a real-world bioprocessing scenario.

Key outcomes:

• Clean, analyze, and visualize complex datasets with Python

• Apply machine learning models for classification and regression

• Use clustering and PCA for pattern recognition and dimensionality reduction

• Implement AI-based optimization strategies for bioprocess workflows

This course is ideal for scientists, engineers, and curious professionals across any industry interested in using Python and data analytics to drive smarter decisions.