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https://github.com/southernmethodistuniversity/ds_1300

Computers, algorithms, and data.
https://github.com/southernmethodistuniversity/ds_1300

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Computers, algorithms, and data.

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DS1300: A Practical Introduction to Data Science — DS 1300




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DS1300: A Practical Introduction to Data Science#


We live in a world driven by computers, algorithms, and data. This
course seeks to equip students with the basic knowledge and skills to
not only understand but to use the tools needed to model and make
decisions about the world around them. Students will be introduced to
basic programming in Python, high-performance computing using ManeFrame
II, and data science.

Using Anaconda#

Installing and Loading Anaconda#


This step can be skipped when using SMU HPC clusters as Anaconda is already
installed and available via module load conda.


Directions for installing Anaconda on your own machine can be found
here.
Either the full Anaconda or the miniconda distributions will work. The
differences between the two are noted on the installation page. More
information on getting started can be found
here.

Installing the ds_1300 Environment#



  1. mamba env create -f environment.yml --force


Using the ds_1300 Environment#



  1. mamba activate ds_1300 to start (source activate ~/.conda/envs/ds_1300
    on M2)


  2. mamba deactivate when finished


Remove Environment#



  1. mamba remove --name ds_1300 --all


Using Python Environments#

Loading a Python Environment#


There are many Python 3 installations on SMU HPC clusters. An example from M3
is given:



module purge

module load gcc python

Installing the ds_1300 Environment#



python3 -m venv ~/.venv/ds_1300

source ~/.venv/ds_1300/bin/activate
pip install --upgrade pip wheel
pip install -r requirements.txt

Using the ds_1300 Environment#



  1. source ~/.venv/ds_1300/bin/activate to start


  2. deactivate when finished


Remove Environment#



  1. rm -rf ~/.venv/ds_1300



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