About the course
Data scientists work in teams and it's important for each team member to understand software engineering processes and practices. From requirements gathering to agile development to testing and deployment, the ability to go beyond writing macros and simple scripts is key to both more sophisticated analyses and building reproducible and scalable data investigations and data products. This course, based in Python, will cover fundamental aspects of computer science, good practices in software engineering, and practical aspects of deploying code in production environments. To do this, we will use the Python language, a simple yet elegant general purpose programming language that is well-suited for data analysis and visualization.
Upon successful completion of the course, students will:
- Understand software architecture and design
- Examine agile and hypothesis-driven software development processes
- Identify team roles and workflows in software engineering
- Conduct requirements gathering
- Use Git and Github for version control and collaboration
- Recognize the importance of testing and building test suites
- Understand the legal aspects of software development
- Apply software engineering practices to your data science project
Allen is an adjunct faculty at Georgetown University and is currently pursuing a graduate degree in Computer Science at the University of Maryland at College Park with an emphasis on databases and distributed systems. He is also a faculty member at District Data Labs and is employed by a local d...
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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
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