This course introduces technical communicators to Python as a tool to analyze, organize, and understand textual data. Though the course serves as an introduction to programming in Python, it approaches this introduction through natural language processing (NLP), a group of data-driven processes necessary for computers to understand natural language data. By completing the course, students will familiarize themselves with Python, software documentation, and an NLP basic processes.
This is a four session asynchronous course. Recordings of each session will be opened to students on Monday mornings. Homework assignments will be due later in the week as determined by the instructor. There will also be two live sessions when students can ask the instructor questions in real time.
The intended audience for this course includes technical communication professionals and students looking to understand software development for technical communicators. The course will not be a replacement for a programming course but will introduce participants to basic software development and natural language processing.
• Expose students to basic programming best practice via simple program examples
• Introduce students to topic modelling as a tool to understand natural language patterns
• Provide opportunities to practice documenting software code
• Explain text pre-processing processes
Session 1: Intro and objectives; programming in Python
Session 2: Pre-processing natural language; documenting code
Session 3: Building a rule-based text classifer
Session 4: Topic modeling
Participants must have access to a computer that will allow them to download the Spyder IDE and appropriate Python libraries. Experience with Python would be a plus, but not necessary.