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