| 1. Analyzing Infected Patients Demographics.mp4 | 81.7 MB | ||
| 1. Analyzing Infectious Disease Yearly Trend.mp4 | 86.2 MB | ||
| 1. Calculating Infectious Disease Transmission with SIR Model.mp4 | 58.4 MB | ||
| 1. Cleaning Infectious Disease Dataset by Removing Missing Values & Duplicates.mp4 | 34.8 MB | ||
| 1. Conclusion & Summary.mp4 | 43.2 MB | ||
| 1. Detecting Potential Outliers with Z Score.mp4 | 61 MB | ||
| 1. Epidemiological Modelling with SIR Model.mp4 | 81.3 MB | ||
| 1. Factors That Accelerate the Spread of Infectious Disease.mp4 | 54.9 MB | ||
| 1. Finding & Downloading Infectious Disease Dataset From Kaggle.mp4 | 63.8 MB | ||
| 1. Finding Correlation Between Population & Disease Rate.mp4 | 51.3 MB | ||
| 1. Forecasting Infectious Disease Rate with Time Series.mp4 | 79.2 MB | ||
| 1. Introduction to Biostatistics.mp4 | 72.4 MB | ||
| 1. Introduction to the Course.mp4 | 34 MB | ||
| 1. Mapping Infectious Disease per County with Heatmap.mp4 | 108.7 MB | ||
| 1. Performing Confidence Interval Analysis.mp4 | 28.9 MB | ||
| 1. Public Health Policy Evaluation.mp4 | 81.7 MB | ||
| 1. Setting Up Google Colab IDE.mp4 | 20.2 MB | ||
| 1. Tools, IDE, and Datasets.mp4 | 89 MB | ||
| 1. Uploading Infectious Disease Dataset to Google Colab.mp4 | 15.4 MB | ||
| 1.1 Google Colab IDE.html | 102.4 B | ||
| 1.1 Infectious Disease Dataset.html | 102.4 B | ||
| 1.1 Kaggle.html | 102.4 B | ||
| 1.1 Population Density.html | 102.4 B | ||
| 1.1 Python.html | 102.4 B | ||
| 1.1 SIR Model.png | 512.6 KB | ||
| 1.1 analyzinginfectedpatientsdemographics.py | 1 KB | ||
| 1.1 analyzinginfectiousdiseaseyearlytrend.py | 1.4 KB | ||
| 1.1 cleaninginfectiousdiseasedataset.py | 716.8 B | ||
| 1.1 confidenceintervalanalysis.py | 614.4 B | ||
| 1.1 detectingpotentialoutliers.py | 1 KB | ||
| 1.1 epidemiologicalmodelling.py | 1.8 KB | ||
| 1.1 findingcorrelationbetweenpopulation&diseaserate.py | 819.2 B | ||
| 1.1 forecastinginfectiousdiseaseratewithtimeseries.py | 1.2 KB | ||
| 1.1 mappinginfectiousdiseasepercounty.py | 1 KB | ||
| 1.1 publichealthpolicyevaluation.py | 1.4 KB | ||
| 2. Quick Overview of Infectious Disease Dataset.mp4 | 31.9 MB | ||
| 2. Table of Contents.mp4 | 45.2 MB | ||
| 2.1 Python for Biostatistics.pptx | 1.1 MB | ||
| 2.1 infectiousdiseasedataoverview.py | 409.6 B | ||
| 3. Whom This Course is Intended for.mp4 | 27.4 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 42 total files | |||
Python for Biostatistics: Analyzing Infectious Diseases Data
https://DevCourseWeb.com
Published 10/2023
Created by Christ Raharja
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 22 Lectures ( 3h 7m ) | Size: 1.23 GB
Forecast infectious disease rate, build epidemiological modelling, and map the spread of infectious disease with heatmap
What you'll learn
Learn the basic fundamentals of biostatistics and infectious disease analysis
Learn how to find correlation between population and disease rate
Learn how to analyze infected patient graphics
Learn how to map infectious disease per county using heatmap
Learn how to analyze infectious disease yearly trend
Learn how to perform confidence interval analysis
Learn how to forecast infectious disease rate using time series decomposition
Learn how to do epidemiological modeling using SIR model
Learn how to perform public health policy evaluation
Learn how to calculate infectious disease transmission rate using SIR model
Learn several factors that accelerate the spread of infectious disease, such as population density, herd immunity, and antigenic variation
Learn how to detect potential outliers using Z score method
Learn how to clean dataset by removing missing rows and duplicate values
Learn how to find and download datasets from Kaggle
Requirements
No previous experience in biostatistics is required
Basic knowledge in Python and statistics
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