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Interactive Journalism MA - Advanced Data and Coding module

Module code: JOM299
City University
2017-2018


In this repo you will find all the course material and presentations for the 2017-2018 Advanced Data and Coding Module for City University MA in Interactive Journalism.

Module outline and aims

Digital journalists increasingly need a complex skillset of developer knowledge, as well as a native understanding of application programming interfaces (APIs) and ‘scraping’ of online sources to be able to interrogate and investigate ‘big data’ in the public interest.

This module, which follows on from ‘Introduction to Data Reporting aims to train you to work effectively a professional digital journalist. By the end of this module you will have an advanced knowledge of data journalism, including skills to investigate and interrogate ‘big data’; demonstrate developer skills in a range of coding languages; be able to interrogate application programme interfaces (APIs) and deploy scraping tools; critically evaluate data sets and complex investigations; and appreciate the accountability role of digital data reporting for civil society in advanced democracies.

from the module handbook

What will i be expected to achieve?

Upon successful completion of this module, you will be expected to be able to:

####Knowledge and understanding:

  • Demonstrate a critical understanding of the importance of digital data reporting as aform of accountability journalism in democratic society
  • Display an understanding of the roles, priorities and workflows of journalists, developers, and programmers who work with and enable the publication of digital journalism

####Skills:

  • Use judgment to analyse and evaluate suitable sources of data and datasets
  • Develop suitable problem-solving approaches to address typical challenges in a digitalnewsroom
  • Complexity in the use of skills using technologies application programme interfaces (APIs) and ‘scraping’
  • Demonstrate developer skills in a range of coding languages

Values and attitudes:

  • Display a comprehensive understanding of the ethical responsibilities of sourcing and publishing data
  • Be self-directed in learing and skills-training, particular in coding
  • Be cognisant of ongoing developments in current practice, scholarship and research of developer lead journalism

Week 1 - The basics

The mysterious creature that is the DOM, what a webpage actually is, and using the DevTools.

We'll have a look at the very basics of working with the web. Having done the pre-course work (Codecademy Javascript tutorial), we hopefully won't lost much time. No set-up involved, just simple practical exercises in a web browser

  • Session 1: practical exercises
  • Session 2: more exercises

Week 2 - Working with Python and data

A foundation session in which we'll talk about some basics such as file formats and, er, where do you write code in the first place. We'll rattle through some online resources and communities where you can get help if you're stuck with a problem. During the second session we'll see the basics of the Python programming language.

  • Session 1: file formats, writing code
  • Session 2: intro to Python

Week 3 - Concrete scraping examples in Python

A heavy session made up of short examples we'll study and extract data from.

  • Session 1: simple scraping
  • Session 2: more complex scraping, saving data

Week 4 - R in the newsroom

Armed with our new best friend RStudio, we'll introduce the R programming language and explore the fantastic tidyverse, as well as plotting our first charts.

  • Session 1: the tidyverse
  • Session 2: ggplot

Week 5 - Concrete R exercises

We'll touch on statistics concepts and keep proving how great R is at prototyping and wrangling data and charts.

  • Session 1: data cleaning exercises
  • Session 2: enough stats to keep you out of trouble

Week 6 - More R

???

Week 7 - Into Javascript charts world

An overview of what is data viz and how central D3.js is to the discipline. We'll however pivot quickly towards Highcharts.js for its simplicity. As for the R sessions, we'll work through basic plotting then more complex examples.

  • Session 1: overview of the discipline, Highcharts
  • Session 2: Highcharts + misc explorations

Weeks 8, 9, 10 - Project work

We will go round the room and take questions from students about their final project. Come prepared with actual problems, be happy to work collaboratively and to make progress in class while we tackle challenges collectively, on the big screen. These sessions are usually the time when "ha-ha" moments happen.


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