Overview
Learn Social Media Analytics in Python. Acquire the Combined Skillset of a Data Scientist and Digital Marketer.
Syllabus
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- 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
Taught by
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On-Demand
