There are increasing opportunities for innovation in design and construction with potential increases in quality and safety. However, most data scientists are not civil engineers and most civil engineers are not data scientists which can cause a disconnect between the engineering problem and the data science problem.

Engineering managers are increasingly required to provide budgets for, and oversee aspects of the development of innovative data products. Knowing the questions to ask to ensure the delivered data product solves the engineering problem (and knowing its limitations) are critical if such tools are to be seriously adopted. This webinar will draw from the presenter's experience as both a structural engineer and data scientist to deliver a unique learning experience. The following areas will be covered:

1. What is Data Science?
2. How do Data Scientists work – tools, frameworks, algorithms, methods.
3. How to express the engineering problem as a data science problem
4. Data procurement and augmentation strategies
5. Asking useful technical questions
6. When to use deep learning vs. other machine learning methods
7. Validation and verification of data products

This session is aimed at engineers who are looking to either develop or oversee the development of machine learning tools internally, or through interfacing with external data science providers.