Python Practice is a working group on the UC Berkeley campus, sponsored by the D-Lab. We hold informal weekly meetings teaching and learning about different topics in the Python programming language, especially for social science, data science, and visualization.

This is ideal for learners who are new to Python — you'll have a group of peers instead of being by yourself. If you're a little more advanced, you can try to teach something. You are welcome to attend any or all meetings throughout the semester.

You can check out or improve our learning resources. We also have a list of topics from past meetings. Please send an email or join us on Mondays from 4:00-5:30pm at D-Lab (356 Barrows Hall, UC Berkeley). 

Coordinators: Megan Carey (mcarey@berkeley.edu) and Liza Praprotnik (liza.praprotnik@berkeley.edu) 

The emerging discipline of Learning Analytics represents a unique opportunity to build bridges between campus researchers, research computing, and teaching and learning software and practitioners (see https://solaresearch.org/). The Berkeley Learning Analytics Group aims to nurture these connections through discussions, panels, and speakers focused on key issues in the field and the promotion of relevant campus projects.

Learning Analytics is a relatively new field in big data analysis that focuses on the user activities captured in the broader learning environment. Transactional and real time system events, which have usually been recorded for system administration purposes, when combined with traditional business intelligence data, are now being recognized as a major foundational component of various “student success” initiatives and services that aim to promote retention, remediation, and improved learning outcomes. See http://tinyurl.com/z6f75ao for a visual of the intersections between user event and demographic, academic, and financial data.

Upcoming Meetings: 

Tuesday, March 21, 4:30-5:30pm

Tuesday, April 4, 2016, 4:30 - 5:30pm

Tuesday, April 18, 2016, 4:30 - 5:30pm

Tuesday, May 2, 2016, 4:30 - 5:30pm

While some of you have familiarity with the wider definition of Learning Analytics, there are many readily available sources to provide additional background.

We ask that you register for the meeting to ensure that there is adequate space and seating.

Looking forward to seeing you there!

So you’ve got some of your graduate classes under your belt, and it's time to begin an original research project. But how exactly are you going to go about surveying voters in Tanzania, interviewing public health officials in France, or running focus groups with seasonal farm workers in the Central Valley? How will you decide whom to speak to, efficiently collect your data, and handle the challenges of working far from home (or even close to home)?  

The Research in Practice Working Group will cover the logistics and ethics of collecting both quantitative and qualitative data in a diverse range of settings. We aim to provide support to graduate students across many disciplines, including the social sciences, public policy, and public health. We will provide a mixture of workshops on specific research tools (such as software for computer-assisted interviewing) and panel discussions on various aspects of the research process (such as hiring research assistants, doing archival research, and thinking through the ethics of doing research in low income countries). We’ll also hold more informal meetings where students can come together and discuss their work.  

This semester we will have sessions on the following evenings: 

• Februrary 28
• March 14
• April 11
• April 27
• May 9

Feel free to contact Justine Davis (justine.davis@berkeley.edu) and Allison Grossman (allison.grossman@berkeley.edu) with any questions. See you soon!

Are you slugging through your weekly stats assignments?

Are you trying to familiarize yourself with Stata to work on your thesis?

Are you an overachiever and just curious about the wonders of statistical programming?

If you don’t want to struggle through learning Stata alone, we’re here.

The Stata Practice Working Group holds informal weekly meetings, steadily working our way through the Stata programming language. It’s ideal for beginners to Stata working in the social and data sciences.

BONUS:  Are you already super savvy in Stata and feeling generous? Come join us and help your fellow bears out.  

Please send us an email or join us on Mondays from 2:30 to 3:30 pm next to the D-Lab in 371 Barrows Hall.

Coordinator: Tisa Barrios Wilson (tbarrioswilson@berkeley.edu)

Are you slugging through your weekly stats assignments?

Are you trying to familiarize yourself with Stata to work on your thesis?

Are you an overachiever and just curious about the wonders of statistical programming?

If you don’t want to struggle through learning Stata alone, we’re here.

The Stata Practice Working Group holds informal weekly meetings, steadily working our way through the Stata programming language. It’s ideal for beginners to Stata working in the social and data sciences.

BONUS:  Are you already super savvy in Stata and feeling generous? Come join us and help your fellow bears out.  

Please send us an email or join us on Mondays from 2:30 to 3:30 pm next to the D-Lab in 371 Barrows Hall.

Coordinator: Tisa Barrios Wilson (tbarrioswilson@berkeley.edu)

Python Practice is a working group on the UC Berkeley campus, sponsored by the D-Lab. We hold informal weekly meetings teaching and learning about different topics in the Python programming language, especially for social science, data science, and visualization.

This is ideal for learners who are new to Python — you'll have a group of peers instead of being by yourself. If you're a little more advanced, you can try to teach something. You are welcome to attend any or all meetings throughout the semester.

You can check out or improve our learning resources. We also have a list of topics from past meetings. Please send an email or join us on Mondays from 4:00-5:30pm at D-Lab (356 Barrows Hall, UC Berkeley). 

Coordinators: Megan Carey (mcarey@berkeley.edu) and Liza Praprotnik (liza.praprotnik@berkeley.edu) 

The emerging discipline of Learning Analytics represents a unique opportunity to build bridges between campus researchers, research computing, and teaching and learning software and practitioners (see https://solaresearch.org/). The Berkeley Learning Analytics Group aims to nurture these connections through discussions, panels, and speakers focused on key issues in the field and the promotion of relevant campus projects.

Learning Analytics is a relatively new field in big data analysis that focuses on the user activities captured in the broader learning environment. Transactional and real time system events, which have usually been recorded for system administration purposes, when combined with traditional business intelligence data, are now being recognized as a major foundational component of various “student success” initiatives and services that aim to promote retention, remediation, and improved learning outcomes. See http://tinyurl.com/z6f75ao for a visual of the intersections between user event and demographic, academic, and financial data.

Upcoming Meetings: 

Tuesday, March 21, 4:30-5:30pm

Tuesday, April 4, 2016, 4:30 - 5:30pm

Tuesday, April 18, 2016, 4:30 - 5:30pm

Tuesday, May 2, 2016, 4:30 - 5:30pm

While some of you have familiarity with the wider definition of Learning Analytics, there are many readily available sources to provide additional background.

We ask that you register for the meeting to ensure that there is adequate space and seating.

Looking forward to seeing you there!

The emerging discipline of Learning Analytics represents a unique opportunity to build bridges between campus researchers, research computing, and teaching and learning software and practitioners (see https://solaresearch.org/). The Berkeley Learning Analytics Group aims to nurture these connections through discussions, panels, and speakers focused on key issues in the field and the promotion of relevant campus projects.

Learning Analytics is a relatively new field in big data analysis that focuses on the user activities captured in the broader learning environment. Transactional and real time system events, which have usually been recorded for system administration purposes, when combined with traditional business intelligence data, are now being recognized as a major foundational component of various “student success” initiatives and services that aim to promote retention, remediation, and improved learning outcomes. See http://tinyurl.com/z6f75ao for a visual of the intersections between user event and demographic, academic, and financial data.

Upcoming Meetings: 

Tuesday, March 21, 4:30-5:30pm

Tuesday, April 4, 2016, 4:30 - 5:30pm

Tuesday, April 18, 2016, 4:30 - 5:30pm

Tuesday, May 2, 2016, 4:30 - 5:30pm

While some of you have familiarity with the wider definition of Learning Analytics, there are many readily available sources to provide additional background.

We ask that you register for the meeting to ensure that there is adequate space and seating.

Looking forward to seeing you there!

So you’ve got some of your graduate classes under your belt, and it's time to begin an original research project. But how exactly are you going to go about surveying voters in Tanzania, interviewing public health officials in France, or running focus groups with seasonal farm workers in the Central Valley? How will you decide whom to speak to, efficiently collect your data, and handle the challenges of working far from home (or even close to home)?  

The Research in Practice Working Group will cover the logistics and ethics of collecting both quantitative and qualitative data in a diverse range of settings. We aim to provide support to graduate students across many disciplines, including the social sciences, public policy, and public health. We will provide a mixture of workshops on specific research tools (such as software for computer-assisted interviewing) and panel discussions on various aspects of the research process (such as hiring research assistants, doing archival research, and thinking through the ethics of doing research in low income countries). We’ll also hold more informal meetings where students can come together and discuss their work.  

This semester we will have sessions on the following evenings: 

• Februrary 28
• March 14
• April 11
• April 27
• May 9

Feel free to contact Justine Davis (justine.davis@berkeley.edu) and Allison Grossman (allison.grossman@berkeley.edu) with any questions. See you soon!