VPYT6000 Python Programming and Data Science for Journalists Emneplan

This course is an introduction to principles of Python Programming and Data Science.

Most journalists do not have a solid quantitative background\and face difficulties when analysing data independently. This difficulty represents a major drawback in journalistic research. Journalists waste time learning analytical methods by themselves that could be more quickly learned with proper instruction and support. As consequence, the quality of insights and research productivity suffer. This course provides a comprehensive introduction to data science and big data applied to investigative journalism.

One of the skills that are crucial for implementing and conducting Data Science projects is the knowledge of programming. This course focuses on the development of basic programming techniques, analytical thinking, comprehension of code, and problem-solving skills achieved through a programming-based approach. It aims to develop basic programming skills relevant for professional use within the realm of journalism.

The content is designed to train the participants in state-of-the-art techniques in data analysis. This will enable the students to interact independently with the data and draw insights from them. This is a hands-on course where the students will learn from implementing the analysis themselves with close supervision. The course will focus on case studies using data from real cases; advanced students may choose to use their own data. The students will develop understanding through constant presentation of their work and dialectical reflection over their choices, results, and interpretations.

Language of instruction is English.

Ingen info

After completing the course, the student should have the following overall learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student knows:

• basic theoretical and practical aspects of data management and data processing for different data types.
• how statistics, dimensionality reduction, and supervised and unsupervised learning may be applied to data analysis in investigations.
• basic data visualization techniques and how to employ them in exploratory data analysis and scientific communication.

The student has:

• an understanding of what an algorithm is and the ability to use algorithmic problem-solving to address real-life problems in business and administration
• basic knowledge of how processes within the realm of journalism can be automated using software
• insight in how software is written, and an understanding of various types of programming languages and their function in various areas of business and administration.

Skills

The student can:

• apply data analysis techniques to collect data, pre-process it, analyse it, and reach conclusions about the data.
• identify and define a problem and craft a solution using data analytics.
• critically assess the results as well as justify and explain the methodological choice.

The student has acquired an ability to:

• format and write basic code
• explain how problem-solving principles are used in programming
• understand how to frame and elicit unstructured business and/or administration problems to solve them through programming.

General competence

The student can apply:

• data analysis principles to data in research.
• methods and tools for data analysis and visualization.

The student:

• is proficient in planning and implementing a project plan for software development for journalism
• is familiar with basic theoretical and practical aspects of data management and data processing for different data types.
• is familiar with basic data visualization techniques and how to employ them in exploratory data analysis and scientific communication.

The course is assembly-based, encompassing two full day gatherings that necessitate in-person presence on campus, and four online gatherings.

The course will take a hands-on learning approach in addition to learning the theoretical concepts. Course participants will work in groups under guidance on a project relevant to journalism.

Følgende arbeidskrav må være godkjent før eksamen kan avlegges:

• Oppgave 1: Vurdere kompetansebehov og planlegge opplæring i egen virksomhet. Skriftlig dokumentasjon, individuell eller i grupper på to til fem studenter. Omfang: 1000 til 2000 ord.
• Oppgave 2: Sammenligne og vurdere hvordan Kompetanse, planlegging og utvikling finner sted i ulike virksomheter. Skriftlig gruppeinnlevering. Omfang: 1000 til 3000 ord.

Arbeidskrav som ikke blir godkjent kan omarbeides én gang.

Faglig aktivitet med krav om deltakelse

Det er krav om 80 % obligatorisk deltakelse på fellessamlinger for å kunne gå opp til eksamen. Fravær ut over 20 % må kompenseres etter avtale med faglærer.

Mappen består av begge arbeidskravene og et refleksjonsnotat knyttet til det faglige innholdet og teorien i emnet. Omfang på refleksjonsnotatet: 1500 til 2000 ord.

Ny/utsatt eksamen

• Ved ny og utsatt eksamen leveres omarbeidet versjon av eksamensmappen.
• Studentens rettigheter og plikter ved ny/utsatt eksamen framgår av forskrift om studier og eksamen ved OsloMet - storbyuniversitetet

Alle hjelpemidler tillatt

En intern sensor. Tilsynssensor evaluerer vurderingsformer og vurderingsprosesser i studieprogrammet.

• Roller og kommunikasjon i ulike typer grupper
• Kartlegging av medarbeideres kompetanse og læringsbehov på arbeidsplassen
• Analyse av kompetansebehov og kompetansekrav i bedriften/virksomheten
• Planlegging, gjennomføring og vurdering av tiltak for læring og utviklingstiltak
• Bruk av innovative og kreative metoder og digitale verktøy i lærings- og utviklingsarbeid

Target group

This continuing education course is aimed at students working as journalists.

Admission

Admission requires Higher Education Entrance Qualification to Norwegian Universities, including proficiency in English (generell studiekompetanse). Norwegian language proficiency is not required.

Admissions are conducted in accordance with Regulations relating to Admission to Studies at OsloMet.

Qualified applicants will be admitted continuously until the course is full. Some study places may be reserved for students recruited by or through partners of OsloMet.