Tickets

The first few weeks of this course function as an intensive onboarding period, similar to what you would experience as a new hire in a biotech startup or a graduate research lab. This phase is designed to bridge the gap between “coding for homework” and “coding for production.”

You will complete three skill certification tickets. These are not standard homework assignments; they are pass/fail competency checks. You have unlimited attempts before the end of Week 5 (Feb 13). Each ticket is worth 5% of your final grade. In the unlikely event you are unable to pass a ticket, you will receive a zero.

Remote Computing Ticket

To earn this ticket, you must demonstrate that you can step away from the comfort of a graphical user interface (GUI) and operate in a remote Linux environment. You will show the instructor that you can

• Establish an SSH connection to the university’s computing cluster;
• Navigate the file system entirely via the command line;
• Manage software dependencies by building an isolated Pixi environment;
• Edit a Python script in the terminal that performs the described computations;
• Write and submit a SLURM script to run this generation task on the compute nodes.

In-person evaluation

Data Insights Ticket

You will prove your ability to transform raw biological data into interpretable insights using the industry-standard Python scientific stack. You will be required to write a Python script that analyzes the output file from the Remote Computing Ticket. You must programmatically clean the data and calculate key descriptive statistics. You must demonstrate the ability to visualize the data by programmatically generating a publication-quality figure using matplotlib. This figure must be self-explanatory, featuring proper axis labels and legends.

Submitted for evaluation

You will submit your single Python script and the resulting .png figure. The instructor will verify that the figure is readable, accurate, and generated entirely by the code provided in a single Python script.

Reproducible Code Ticket

This ticket your ability to write code that others can actually use and build upon. You will take the data generation script from Remote Computing Ticket and the analysis script from the Data Insights Ticket and refactor them into a cohesive pipeline.

You must move away from hard-coded file paths and demonstrate the ability to write modular Python scripts that accept input files and parameters via command-line arguments. Your script must be flexible enough to handle different inputs without requiring the user to edit the source code. You will house this work in a properly initialized Git repository, keep the repo clean of data trash, and a README.md that serves as a clear user manual for running your pipeline. You must verify your version control hygiene by committing your work with meaningful messages and pushing it to a remote GitHub repository, simulating a collaborative workflow.

Submitted for evaluation

The test here is strict reproducibility. You will send your repository URL to the instructor, who will clone it to a fresh machine. The instructor will attempt to run your pipeline using only the instructions provided in your README. If the script runs immediately and produces the correct output without manual debugging or file path errors, you pass.