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This repository stores the slides and code examples for the workshop "Invitation to Python" at HKBU, 24 Nov 2018

License: MIT License

Jupyter Notebook 100.00%

201811_budmc_invitation2py's Introduction

Invitation to Python: Programming for news, culture, and social justice

This repository stores the slides and code examples for the workshop "Invitation to Python" at HKBU, 24 Nov 2018.

About the workshop

This one-day workshop, offered by the Data and Media Communication Concentration, attempts to explore fundamental issues on the intersection of programming, data science, and data-driven journalism, and public expression. It will also make a whirlwind tour of Python. Topics include package installation, program execution, Python variables, expressions, data structures, functions, and fundamentals of control flow statements.

By the end of the workshop, students will have a preliminary understanding of data science in the context of media and communication, and preparatory knowledge of Python. It aims to lay the foundation for advanced data and media communication courses, such as Data Analysis Studio, Exploratory Data Analysis and Visualization, Data Media Projects, and the proposing interactive DMC news platform.

Content

Section 1. Introduction (Slides)

  1. who, what, How
  2. why programming
  3. digital and media education at a glance
  4. articulating an interdisciplinary knowledge hub

Section 2. Tool installation (Slides)

  1. Python 3.x
  2. Anaconda
  3. Markdown language
  4. Jupyter Notebook (aka Python in a notebook)

Section 3. A Byte of Python (Notebooks)

  1. "computational thinking"
  2. Python programme execution
  3. variables and expressions
  4. data types
  5. data structures - list - dictionary - tuple - set
  6. functions
  7. control flow statements (issue: indentation) - The conditions (if, else, elif) - The loops (for, while, try and except)

Section 4. Data science in Action (not covered today - it will RETURN!)

  1. the problem, the question, and the motivation
  2. four of the many approaches to find a story
  3. present a story
  4. Wrapping up

About the speaker

Dr Xinzhi ZHANG (M.A. & Ph.D., CityU HK) is a Research Assistant Professor at JOUR. His research interests include comparative political communication, emerging technologies and social change, digital humanities, and data-driven journalism. His research works have been published on journals such as Computers in Human Behavior, International Political Science Review, and Digital Journalism. He has taught several storytelling courses such as Multimedia Communication (broadcasting and online media), Films and Storytelling (scripts and narrative), Languages, Cultures, and Communication (text and discourse), and Social Media Data Acquisition and Processing with Python (Course Repo). He now works for the Data and Media Communication Concentration at JOUR.

Acknowledgement

We shall give a big applaud to Dr Li Chen, the coordinator of DMC at the Department of Computer Science, who is very considerate to propose this workshop; and Dr Liang Lan from COMP, who previewed all the slides and codes and offered some comments. Mr Xu Chen (BSc CS, COMP) and Miss Can He (MSc ITM, COMP) tested all the codes and shared several suggestions from the perspective of a (CS) student; and of course, we shall thank Miss Ripple Yuan, the PA of DMC who carefully organized this workshop.

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