Technical Report Preparation

Published

August 22, 2026

Technical Report Preparation

Each lab exercise will have an associated technical report submitted. These reports will be prepared and submitted using Python-based Jupyter notebooks that will be included as part of your assignment git repositories.

You will need to be able to perform the following tasks in your Jupyter notebooks:

  • Read CSV text data saved from an oscilloscope.

  • Perform signal processing (e.g., FFT, filtering, etc.) on the data.

  • Perform simple statistics (e.g., mean, standard deviation, 95% CI) on the data.

  • Generate plots

Python Virtual Environment

Preparing your technical reports will require either:

  1. Using a cloud-based Jupyter notebook platform (e.g., Google CoLab), or
  2. Use a local Python virtual environment on your laptop with the necessary packages installed.

If you need to install a Python environment on your laptop, then this is a good starting point: Getting Started with Python in VS Code.

This is a good tutorial on getting started with Jupyter notebooks in VS Code: Jupyter Notebooks in Visual Studio Code.