Unlocking Media Trends with Big Data Technology

Overview

Imagine knowing exactly which film genre will capture audiences’ attention or understanding social media trends before they go viral. Data analysis makes this possible.

Syllabus

• Introduction to Big Data and Media
Overview of Big Data
Importance of Big Data in Media
Case Studies: Success Stories in Media Using Big Data
• Understanding Media Data Sources
Social Media Analytics
Streaming Services and Viewing Data
News and Online Content Analysis
• Data Collection Techniques
Web Scraping for Media Data
APIs and Real-Time Data Access
Data Ethics and Privacy Concerns
• Data Processing and Cleaning
Handling Large Datasets
Data Cleaning and Preparation
Tools for Data Processing (Python, R)
• Data Analysis Techniques
Descriptive Analytics in Media
Predictive Modeling for Trending Topics
Sentiment Analysis
• Identifying Media Trends
Trend Detection Algorithms
Image and Video Content Analysis
Natural Language Processing in Media
• Machine Learning Applications
Recommender Systems for Media Content
Clustering and Classification in Media Datasets
Case Studies of Machine Learning in Media
• Visualization and Communication of Insights
Data Visualization Tools (Tableau, Power BI)
Storytelling with Data in Media
Effective Communication of Data-Driven Insights
• Project: Media Trend Analysis
Project Proposal and Data Selection
Data Analysis and Trend Prediction
Presentation of Findings and Recommendations
• Conclusion and Future Trends
Emerging Technologies in Big Data and Media
The Future of Media Consumption and Engagement
Preparing for a Career in Data-Driven Media Analysis

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Taught by

Yuhan Liu

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Subjects

Data Science