Data Science AI-Assisted Development Workshop: Practices and Pitfalls

AI coding tools are reshaping data science and software engineering. Whether you end up in data analytics, ML engineering or somewhere in between, fluency with these tools and a clear-eyed understanding of their risks are quickly becoming non-negotiable.

This isn't a topic you can figure out later. The landscape is changing rapidly, opinions are sharply divided, and yet proficiency with these tools is quickly becoming an expected skill. The choices you make and habits you form now will have real consequences for your work and career. Frameworks for navigating all of this are currently lacking so there is fertile ground for exploration and discussion.

This one-day, hands-on data science workshop covers the practical, ethical, and career dimensions of AI-assisted software development.

By the end of this workshop, you’ll be able to:

• Learn effective prompting strategies and best practices for working with agents like Claude Code or Copilot
• Gain techniques for verifying AI-generated code
• Grapple with the hard questions including: privacy risks, vendor dependency, intellectual property and environmental impact
• Understand what these AI coding tools mean for the future of technical careers

Basic knowledge of any coding language such as Python, R, SQL, or Javascript and working with data analytics is required.

Course outline

• Module 1: Welcome, Framing and Context
• Module 2: How These Tools Work
• Module 3: Effective and Responsible Use
• Module 4: Risks and Responsibility
• Module 5: Running Models Locally
• Module 6: Your Career in the Age of AI-Assisted Development
• Benefits vs. Risks Comparison Framework

How am I assessed?

This course is marked complete/incomplete, and is based on your attendance and participation.

Expected effort

Expect to spend the full six-hour day in class including lunch and short breaks.

Technology requirements

To take this course, and for the best experience, we recommend you have access to:

• an email account
• a computer, laptop or tablet
• the latest version of a web browser (or previous major version release)
• a reliable internet connection
• a video camera and microphone.

The day before your course starts, you will receive an email with instructions on how to access the course.

Requisites

Experience with data analytics and exposure to any coding language (Python, R, SQL, Javascript, etc.).

Course format

The one-day workshop is offered both online and in-person formats.

In-person will take place at Robson Square in Downtown Vancouver. At the same time, those participating online will log in to the class at the scheduled time and participate by Zoom.