Corporate Course Catalog

Gain hands-on coding experience and foundational knowledge of how use Python and key scientific Python libraries for data processing, analysis, and visualization.

Data is a valuable scientific resource. In this course you will learn best practices about data stewardship as well as the digital skills needed to store, retrieve, and manage data.

While learning the technical Python skills required to effectively store and retrieve data from text files

From an overview of a typical data analysis workflow and foundational ideas, apply your understanding of major concepts through exercises with NumPy, Pandas, and XArray. Through a practicum, develop a data analysis workbook that can be applied in real-world projects.

Survey, explore, and create explanatory visualizations that facilitate communications with multiple techniques for visualizing data. By the end of the course, apply new skills to create a Jupyter notebook for exploring and explaining a scientific data set.

Acquire skills in the basics of machine learning using problems drawn from science and engineering data sets. The course focuses primarily on supervised learning, regression, classification, and unsupervised machine learning strategies.

Gain a practical introduction to deep learning using Keras and TensorFlow with focus on the fundamental model architecture: the neural network.

In this short course on the critical art of writing maintainable software, learn best practices for making quality software that can be used, referenced, and kept in working order.

This course is a workshop in building a data entry tool and an interactive data visualization tool. Gain practical experience building working desktop applications to assist with R&D efforts.

Discover why web-based tools are great for communicating research results and for sharing analyses and tools with colleagues (without the need to install additional software on a laptop or desktop). Learn the basic technologies of the web and how to interact with them from Python.

In the culminating course of the Manager Track, students are taught how to think about digital transformation in organizations. How do digital skills help transform scientific R&D? What organizational mind-shifts are needed for successful digital transformation? How to lead and foster the di