Hi ,
Data science sits at the intersection of Computer Science and Statistics, so it comes as no surprise that
many of the best data scientists have a computer science or software development background. And those that don’t? Well, there’s a lot they can learn from software developers.
In the latest episode of Value Driven Data Science, I'm joined by software developer/architect Ethan Garofolo, author
of Practical Microservices: Build Event-Driven Architectures with Event Sourcing and CQRS, to discuss techniques from software engineering and software development that you can use to become a better data scientist.
Some of the things we discuss in this episode include:
- What is the difference between a software engineer, software developer and software architect?
- The impact of team structure and communications on software design.
- How Lean and DevOps principles can be used to make technical teams run more effectively.
- The benefits of pair programming and mob programming.
- What is test-driven
development and how can it be used to enhance the quality of data science outputs?
- Using ChatGPT/AI to enhance developer capabilities.
You can listen to this episode by clicking the button below, or find it on Apple Podcasts, Amazon Music, Spotify or Google Podcasts.
