AI, Data and Communication MA

Program Overview

AI, Data and Communication MA

Overview

The AI, Data and Communication MA is a unique interdisciplinary program that combines media and communications with an accessible introduction to computer science. This course focuses on the critical analysis of data and its impact on society, encouraging students to think creatively about the role of data in various sectors.

Course Structure

The program consists of four core modules and three optional modules, allowing students to tailor their learning experience. The core modules include:

Core Modules

• Data in Communication and Society
• Data Systems Concepts and Fundamentals
• Data and Digital Research Methods
• Major Project

Optional Modules

• Social Media
• Political Economy of Communication
• Data Mining and Machine Learning
• The Politics of Global Complexity
• Artificial Intelligence and Society
• Digital Cultures
• Digital Media and Critical Theory
• Data Visualisation and Dashboarding
• Hack Lab and Creative Technology
• Digital Media Business: Strategy and Entrepreneurship
• Policies for the Digital Age
• Media Futures – Foresight Methods for Media and Content Industries
• Law and Digital Disruption
• Law and Data
• Law and Governance of Technological Risk

Entry Requirements

• A minimum of an upper second class honours degree (2:1) or a lower second class honours degree (2:2) and substantial relevant work experience.
• If the first language is not English, an IELTS 6.5 overall, with at least 5.5 in each element, is required.
• One academic reference is required.

Fees and Funding

• UK tuition fee: £1,125 (Price per 20-credit module)
• International tuition fee: £1,985 (Price per 20-credit module)
• Alumni discount available
• Funding options available, including Student Finance England (SFE) and scholarships

Research Groups

• Centre for Research and Education in Art and Media (CREAM)
• Communication and Media Research Institute (CAMRI)
• Computational Vision and Imaging Technology Research Group

Teaching and Assessment

• Teaching methods include lectures, seminars, workshops, and problem-based learning.
• Assessment types include practical, coursework, and written exams.
• Year 1: 18% scheduled hours, 82% independent study
• Year 2: 15% scheduled hours, 85% independent study

Location

• Harrow Campus, located in north-west London, 20 minutes from the city centre by train.

Related Courses

• Big Data Technologies MSc
• Data Science and Analytics MSc
• Social Media and Digital Communication MA