Understand introductory concepts and terminology for programming with Python and apply them to journalistic tasks.

Write small pieces of code and collaboratively edit them in class with peers.

Undertake tasks of cleaning, analyzing, and processing unstructured and structured data.

Reproduce code from published articles.

Visualize and map data at a basic level.

Utilize public sources to develop stories.

Become familiar with modern scientific methodologies and techniques.

Analyze data using Python, basic statistical analysis, OpenRefine, and other introductory tools and skills.

Understand various data formats and methods of storing, accessing, and processing information.

Manage CSV files, interact with website APIs and JSON, identify raw text documents, use regular expressions, perform text mining, and manage SQL databases.

Build web scrapers.

Convert difficult-to-access PDFs into usable information.

Learn protocols (census/research, interviews, crowdsourcing, and experiments), strategies, and computer-assisted tools for data collection.

The course is assessed in the English language.

Assessment includes a written exam with a combination of questions (essay, short answer, multiple choice) (40%), coding-based written assignment (40%), research (15%), and bibliography writing (5%).

The syllabus, procedures, and assessment criteria are communicated to students in the first lecture. Relevant announcements and materials are posted on the e-class platform.