Python for Social Media Analytics

Overview

Ready to combine the power of data science with social media marketing and become an invaluable asset to any business?

Syllabus

• Introduction to Python for Social Media Analytics
Overview of Python and its applications in social media
Setting up the Python environment
• Basics of Python Programming
Variables, data types, and basic operations
Control structures: loops and conditionals
Functions and modules
• Data Collection from Social Media Platforms
Using APIs to collect data (Twitter, Facebook, Instagram)
Web scraping basics with BeautifulSoup and Scrapy
• Data Cleaning and Preprocessing
Handling missing data and duplicates
Data transformation techniques
Working with Pandas for data manipulation
• Exploratory Data Analysis (EDA)
Understanding data distribution: plots, histograms, and charts
Identifying trends and patterns in social media data
Visualizing data with Matplotlib and Seaborn
• Natural Language Processing (NLP) for Social Media
Basics of text processing and tokenization
Sentiment analysis on social media posts
Keyword extraction and topic modeling
• Machine Learning for Social Media Analytics
Introduction to machine learning concepts
Building predictive models for engagement metrics
Implementing clustering techniques for user segmentation
• Social Network Analysis
Understanding social network structures
Network visualization and community detection
Analyzing influencer impact using network metrics
• Automation and Real-Time Analytics
Automating data collection and analysis with Python scripts
Real-time dashboards using Streamlit or Dash
Integrating with social media platforms for dynamic insights
• Ethical Considerations and Data Privacy
Understanding ethical issues in social media data analytics
Compliance with privacy laws and regulations
• Final Project
Define a real-world problem involving social media data
Data collection, analysis, and insights presentation

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Taught by

365 Careers

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Subjects

Programming