COVID-19 Data Science Urban Epidemic Modelling in Python
Analyze coronavirus data with spatial analysis, modeling, and visualization techniques. Understand epidemic patterns and trends.
Course Content
COVID-19 Data Science Urban Epidemic Modelling in Python is an all-levels Udemy course taught by Gevorg Yeghikyan. It runs 4h 7m, is taught in English, and includes a certificate of completion. Learners rate it 4.4 out of 5 from 129 reviews, with 781 students enrolled. It is a paid course, last updated February 2021.
Learn spatial data analysis and visualization with Python! This practical course uses the COVID-19 pandemic in Yerevan as a real-world example to teach you how to model and visualize disease spread.
You'll gain hands-on experience using Python (3+), GeoPandas, NumPy, and Matplotlib to:
- Analyze real urban mobility data: Extract insights from actual city movement patterns.
- Model COVID-19 spread: Learn the mathematics behind spatial epidemiological models and implement them in Python.
- Simulate epidemic scenarios: Run simulations of the COVID-19 epidemic using real-world data in Jupyter Notebooks.
- Create animated spatial visualizations: Build compelling, complex animations on a city map to illustrate virus transmission.
- Enhance Python coding skills: Discover tips and tricks to improve your Python programming and data visualization abilities.
Course Sections:
- Introduction to GeoPandas: Master spatial visualization in Jupyter Notebooks using the powerful GeoPandas library.
- Spatial Epidemiological Models: Develop a strong understanding of the mathematical foundations of spatial epidemiology.
- Python Epidemic Simulation: Code an efficient epidemic simulation engine using Python and NumPy.
- COVID-19 Simulation: Apply the simulation model to real urban mobility data to simulate the spread of COVID-19 within a city.
- Interactive Spatial Visualizations: Combine all learned skills to create stunning animated maps visualizing spatial data and epidemiological data.
This course is designed for those with basic Python experience and an interest in data science, spatial analysis, and data visualization. You'll leave with valuable skills in spatial data science ready to apply to your own projects. Get ready to build impactful data visualizations and become proficient in spatial data analysis with Python! Support and guidance are available throughout the course.
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