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This is an archive of our past working groups. We are looking to include working groups topics not yet covered here. Is there something not currently on the list? Send us a proposal.

E.g., 21-Sep-17
E.g., 21-Sep-17
Coordinator:
Evan Muzzall, Chris Kennedy

Although programming aspects of machine learning in R and Python are challenging in themselves, the need to understand fundamental mathematical aspects is obligatory. It is unfortunately common in the social sciences to apply machine learning techniques to solve a particular problem without necessarily understanding their numerical underpinnings.

June 7, 2017 to August 2, 2017
Coordinator:
Evan Muzzall, Chris Kennedy

Although programming aspects of machine learning in R and Python are challenging in themselves, the need to understand fundamental mathematical aspects is obligatory. It is unfortunately common in the social sciences to apply machine learning techniques to solve a particular problem without necessarily understanding their numerical underpinnings.

June 7, 2017 to August 2, 2017
Coordinator:
Evan Muzzall, Chris Kennedy

Although programming aspects of machine learning in R and Python are challenging in themselves, the need to understand fundamental mathematical aspects is obligatory. It is unfortunately common in the social sciences to apply machine learning techniques to solve a particular problem without necessarily understanding their numerical underpinnings.

June 7, 2017 to August 2, 2017
Coordinator:
Evan Muzzall, Chris Kennedy

Although programming aspects of machine learning in R and Python are challenging in themselves, the need to understand fundamental mathematical aspects is obligatory. It is unfortunately common in the social sciences to apply machine learning techniques to solve a particular problem without necessarily understanding their numerical underpinnings.

June 7, 2017 to August 2, 2017
Coordinator:
Evan Muzzall, Chris Kennedy

Although programming aspects of machine learning in R and Python are challenging in themselves, the need to understand fundamental mathematical aspects is obligatory. It is unfortunately common in the social sciences to apply machine learning techniques to solve a particular problem without necessarily understanding their numerical underpinnings.

June 7, 2017 to August 2, 2017

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?

February 28, 2017 to May 23, 2017

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.

January 30, 2017 to May 22, 2017
Coordinator:
Oliver Heyer, John Scott

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/).

March 21, 2017 to May 16, 2017

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?

February 28, 2017 to May 23, 2017

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.

January 30, 2017 to May 22, 2017
Coordinator:
Tisa Barrios Wilson

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.

 

February 27, 2017 to May 8, 2017
Coordinator:
Oliver Heyer, John Scott

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/).

March 21, 2017 to May 16, 2017
Coordinator:
Tisa Barrios Wilson

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.

 

February 27, 2017 to May 8, 2017

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?

February 28, 2017 to May 23, 2017

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.

January 30, 2017 to May 22, 2017
Coordinator:
Tisa Barrios Wilson

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.

 

February 27, 2017 to May 8, 2017
Coordinator:
Oliver Heyer, John Scott

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/).

March 21, 2017 to May 16, 2017
Coordinator:
Tisa Barrios Wilson

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.

 

February 27, 2017 to May 8, 2017

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?

February 28, 2017 to May 23, 2017

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.

January 30, 2017 to May 22, 2017

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