Data Visualization with Python
( 30 Modules )

Module #1
Introduction to Data Visualization
Overview of data visualization, importance, and uses

Module #2
Python Basics for Data Visualization
Review of Python basics, including data types, libraries, and syntax

Module #3
Introduction to Matplotlib
Overview of Matplotlib, installation, and basic plot types

Module #4
Line Plots and Scatter Plots
Creating line plots and scatter plots with Matplotlib

Module #5
Bar Charts and Histograms
Creating bar charts and histograms with Matplotlib

Module #6
Customizing Plots with Matplotlib
Customizing plot appearance, labels, and legends with Matplotlib

Module #7
Introduction to Seaborn
Overview of Seaborn, installation, and basic visualization types

Module #8
Visualizing Distributions with Seaborn
Visualizing distributions with Seaborns distplot and jointplot

Module #9
Visualizing Categorical Data with Seaborn
Visualizing categorical data with Seaborns countplot and categorical plots

Module #10
Visualizing Regression Analysis with Seaborn
Visualizing regression analysis with Seaborns lmplot and regplot

Module #11
Introduction to Plotly
Overview of Plotly, installation, and basic visualization types

Module #12
Interactive Visualizations with Plotly
Creating interactive visualizations with Plotly

Module #13
3D Visualizations with Plotly
Creating 3D visualizations with Plotly

Module #14
Data Preparation for Visualization
Preparing data for visualization, including cleaning, transforming, and aggregating

Module #15
Data Source and Integration
Connecting to data sources, including CSV, Excel, and databases

Module #16
Advanced Visualization Topics
Advanced visualization topics, including geospatial visualization and animation

Module #17
Best Practices for Data Visualization
Best practices for data visualization, including design principles and storytelling

Module #18
Case Studies in Data Visualization
Real-world case studies in data visualization, including examples and applications

Module #19
Working with Big Data and Streaming Data
Visualizing big data and streaming data, including tools and techniques

Module #20
Deploying Data Visualizations
Deploying data visualizations, including options for web, mobile, and print

Module #21
Advanced Data Visualization Tools
Introduction to advanced data visualization tools, including Bokeh and Altair

Module #22
Visualization for Machine Learning
Visualizing machine learning models, including model evaluation and feature importance

Module #23
Visualization for Natural Language Processing
Visualizing natural language processing data, including text and topic modeling

Module #24
Visualization for Time Series Data
Visualizing time series data, including forecasting and anomaly detection

Module #25
Visualization for Geographic Data
Visualizing geographic data, including mapping and spatial analysis

Module #26
Interactive Dashboards
Creating interactive dashboards with Python and data visualization libraries

Module #27
Data Visualization in the Real World
Real-world applications of data visualization, including business, healthcare, and finance

Module #28
Final Project
Final project, where students apply data visualization skills to a real-world problem

Module #29
Appendix:Troubleshooting and Resources
Troubleshooting common issues and additional resources for further learning

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Data Visualization with Python career

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Data Visualization with Python ( 30 Modules )

Data Visualization with Python
( 30 Modules )