❗The content presented here is sourced directly from Futurelearn platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [July 05th, 2023]
This course, Digital Media Analytics: Using Listening Data, provides an overview of the tools and techniques used to analyze digital media data. Participants will learn how to use social listening tools to investigate online sentiment and how quickly messages spread about competitors or other trends on social media. They will also explore off-the-shelf tools and creating bespoke social media listening tools using advanced “API spigots” or tools that tap directly into social media flows. By the end of the course, participants should have a new awareness of tools for social learning and how to turn social listening take into useable business insights. This course is ideal for professionals looking to advance their careers and learn more about social media and digital media analytics.
[Application]
Upon completion of this course, participants can apply their knowledge to create their own social media listening tools, analyze online sentiment, and turn social listening data into useable business insights. They can also use the knowledge gained to develop strategies for their own digital media analytics projects.
[Career Path]
The recommended career path for learners of this course is Digital Media Analytics. Digital Media Analytics is a field that focuses on using data to understand how people interact with digital media, such as websites, apps, and social media platforms. Digital Media Analysts use data to identify trends, measure performance, and optimize user experiences. They use a variety of tools, such as web analytics, social media analytics, and data visualization, to analyze data and make informed decisions.
The development trend of Digital Media Analytics is towards more sophisticated and automated data analysis. As technology advances, Digital Media Analysts are able to use more advanced tools to analyze data more quickly and accurately. Additionally, the use of artificial intelligence and machine learning is becoming increasingly popular in the field, allowing Digital Media Analysts to automate data analysis and make more accurate predictions.
[Education Path]
The recommended educational path for learners of this course is a Bachelor's degree in Digital Media Analytics. This degree program will provide students with the knowledge and skills necessary to analyze and interpret data from digital media sources, such as social media, websites, and other digital platforms. Students will learn how to use data to inform decisions, create strategies, and develop insights. They will also learn how to use data to measure the success of campaigns and optimize digital media performance. Additionally, students will gain an understanding of the ethical implications of digital media analytics and the importance of data privacy.
The development trend of this degree program is to focus on the use of artificial intelligence and machine learning to analyze and interpret data from digital media sources. Students will learn how to use AI and machine learning algorithms to identify patterns and trends in data, as well as how to use these algorithms to create predictive models. Additionally, students will learn how to use AI and machine learning to automate tasks and optimize digital media performance.