Data Science for Managers – Code Bank

Data Science for Managers partners with universities and organizations around the world to provide high-quality boot camps, seminars, and workshops in Data Science.

DSFM courses are currently offered at:

• The Swiss Institute of Technology - EPFL

  Join DSFM at the École Polytechnique Fédérale de Lausanne (EPFL), part of the Swiss Federal Institute of Technology and one of the leading technical centers in Europe. EPFL is home to over 350 laboratories and research groups, each working at the forefront of science and technology.

• The University of Washington - GIX

  Join DSFM at the Global Innovation Exchange (GIX) in the Seattle, Washington area. Founded by the University of Washington, Tsinghua University, and Microsoft, GIX is a global collaboration between leading academic and cross-sector partners. Courses will be presented at the state-of-the-art Steve Ballmer building in Bellevue, WA.

• For more information on DSFM, please visit https://www.dsfm.org

Code Bank Materials

The DSFM program provides open access to the Code Bank at https://github.com/dsfm-org/code-bank.git under a free MIT License.

The Code Bank is organized into the following folders. All code is ready for execution, with the exception that code in the _beta/ directory is still in review and testing.

• Illustrations

  Illustrations are short portions of programming code to demonstrate a concept covered in a lecture. Each illustration may take 5 to 10 minutes to complete. The emphasis when showing an illustrations is not on the code, syntax, or libraries used - but rather on the concepts that are being taught. When showing an illustration, the idea is to jump over the code and show the result(s) of what the code does.

• Demos

  Demonstrations cover a topic in more depth than an illustration; here, there is more emphasis on the code, syntax, and libraries that are being used. Each demo generally takes 45 to 90 minutes to complete. The emphasis in a demo is to walk the students through an extended example, going step-by-step, so they see a complete example of solving a particular problem.

• Exercises

  Exercises require students to solve short problems on their own. Exercises do not require long logical chains to complete. The emphasis of an exercise is to push students to look through other code that they have covered elsewhere in DSFM (say in Demos and Illustrations) in order to find snippets of code that they can re-purpose to solve a new problem.

• Projects

  Projects asks students to work through an entire Data Science application. Projects do not require students to program all of it (doing so would not be feasible during the available time in boot camp courses); rather, projects focus attention on discrete portions of code to be completed, while the missing piece is embedded within a longer chain/logical progression of code.

• Workshops

  Whereas code from the Illustrations, Demos, Exercises and Projects can be used a la carte to meet the needs of a particular course of instruction, the materials for a workshop combine as a set to cover a particular topic or application in depth.

Installation & Execution

1. Install Python 3.7.

   Download and install Anaconda Python 3.7.

2. Clone the Code Bank.

   git clone https://github.com/dsfm-org/code-bank.git

3. Install the Python requirements.

   cd code-bank

   pip install -r REQUIREMENTS.txt

4. Execution

   Most of the code in the Code Bank runs in Jupyter Lab notebooks. Most notebooks can be run locally (or remotely) on a standard computer with Python 3.x and a basic Anaconda Data Science environment (see requirements). A few advanced examples, however, may require additional memory, processors, GPUs/TCUs, a Spark cluster, or other resources to run. If additional resources are required, it should be noted in the file.

   We often recommend that students use a virtual machine (VM) to run their code. We provide an additional readme file in the vms/ to help you set up a VM on the Google Compute Platform.

The DSFM Code Bank is an Open Source Initiative !

The Data Science for Managers Network distributes all of code used in DSFM demos, exercises, illustrations, projects, and workshops for free use by the creative commons. You may access, download, clone, edit, reuse, and collaborate on all of the materials in this repository under a free MIT License. Please see the contributing page if you would like to contribute back to this initiative.