Frequently Asked Questions
General Questions¶
Q: How much does it cost to adopt Data 6?
A: The course materials are completely free. You’ll need institutional support for computing infrastructure (JupyterHub) and LMS (Canvas), which most institutions already have. We can help you set up JupyterHub if your institution doesn’t have one.
Q: Can I modify the materials for my institution?
A: Yes! The public materials are available for you to adapt and customize. We only ask that you don’t distribute solutions publicly to protect the integrity of the course materials for all institutions.
Q: What if I don’t have JupyterHub at my institution?
A: We can help you set one up, or you can use alternative platforms like Google Colab, Binder, or your institution’s existing computing infrastructure. Contact us at data6@berkeley.edu to discuss options.
Q: How long does the adoption process take?
A: Typically 2-4 weeks from initial contact to full deployment, depending on your institution’s IT processes. The timeline includes:
Completing the Instructor Interest Form (1 day)
Getting access to private repositories (1-3 days)
Setting up JupyterHub (1-2 weeks, depending on your IT)
Configuring Canvas and grading (3-5 days)
Q: Do I need to be at a specific type of institution?
A: No! Data 6 is designed to be adaptable. While we particularly support community colleges and smaller institutions through NSF funding, the materials can be used at any educational institution.
Technical Questions¶
Q: What technical skills do I need to teach Data 6?
A: You should be comfortable with Python programming and basic data analysis concepts. Familiarity with Jupyter notebooks is helpful but not required. We provide training materials and support.
Q: What version of Python does Data 6 use?
A: Data 6 uses Python 3 with standard data science libraries (pandas, numpy, matplotlib, etc.). The course materials specify exact package versions for reproducibility.
Q: Can I use a different LMS besides Canvas?
A: Yes! While we provide a Canvas template, the materials can be adapted for other LMS platforms. The core notebooks work independently of the LMS.
Q: What about accessibility and privacy requirements?
A: We provide HECVAT (privacy) and VPAT (accessibility) documentation. Jupyter accessibility is an ongoing effort, and we’re committed to making the materials accessible. See the Adoption Guide for more details.
Grading Questions¶
Q: Do I have to use automated grading?
A: No, but it’s highly recommended. Automated grading saves significant time and provides consistent feedback. We support three options: Otter Service Standalone (web-based), GradeScope (paid service), or local grading. See the Grading section for details.
Q: How does the grading service work?
A: Students submit their notebooks, and the grading service automatically executes tests and checks outputs. Grades are exported to CSV format for easy import into your LMS. The process typically takes about 1 minute per 10 notebooks.
Support Questions¶
Q: What kind of support do you provide?
A: We provide:
Access to private solution repositories
Canvas template and setup assistance
JupyterHub configuration help
Grading infrastructure support
Community forum and email support
Q: Can I get training on how to teach Data 6?
A: Yes! We offer workshops and can provide training materials. Contact us at data6@berkeley.edu to discuss training options.
Q: What if I run into problems during setup?
A: Contact us at data6@berkeley.edu. We’re here to help troubleshoot issues and can often resolve problems quickly.
Course Content Questions¶
Q: How is Data 6 different from Data 8?
A: Data 6 focuses specifically on computational thinking for data science and society, with a stronger emphasis on social science applications and computational social science. Data 8 is more general-purpose data science. Both courses complement each other.
Q: What prerequisites do students need?
A: Data 6 is designed as an introductory course. No prior programming experience is required, though basic math skills are helpful.
Q: How many students can the course accommodate?
A: The course has been taught to classes ranging from 20 to 200+ students. The infrastructure scales well, and we can help you plan for your class size.
Q: Can I see examples of student work?
A: We don’t share student work publicly, but we can provide sample assignments and solutions (with access) to help you understand the course level and expectations.