What will you learn in COVID19 Data Analysis Using Python Sheets Course
Prepare and preprocess COVID-19 and life-factors datasets.
Choose and calculate meaningful measures for analysis.
Merge datasets and find correlations.
Visualize results using Seaborn charts.
Work hands-on with pandas, Matplotlib, and Seaborn in a split-screen, browser-based environment.
Program Overview
Module 1: COVID-19 Data Analysis Using Python
⏳ 100 minutes
Topics: Import and preprocess COVID-19 and World Happiness datasets; Merge datasets, calculate metrics, explore correlations, and visualize with Seaborn
Hands-on: Load and clean data; Drop unnecessary columns and aggregate rows; Compute analysis measures; Merge datasets; Generate correlation plots using Seaborn
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Job Outlook
Builds practical data analysis and visualization skills for data-driven roles.
Ideal for careers like Data Analyst, Data Scientist, Health Data Analyst, or Epidemiologist.
Particularly valuable in public health, research, and policy sectors.
Entry-level data roles in India often range around ₹5–10 LPA; internationally, they span $50,000–$90,000 USD.
Specification: COVID19 Data Analysis Using Python Course
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FAQs
- Basic Python familiarity and Jupyter Notebook experience are sufficient.
- Course focuses on data analysis, not deep programming.
- Uses preloaded datasets for hands-on learning.
- Step-by-step guidance helps beginners follow along.
- Ideal for those seeking practical Python applications in data analysis.
- Work with real-world COVID-19 and World Happiness datasets.
- Merge multiple datasets for correlation analysis.
- Visualize trends using Matplotlib and Seaborn charts.
- Apply preprocessing and cleaning techniques for reliable results.
- Gain experience relevant to public health and epidemiology roles.
- Use Seaborn for correlation plots and data insights.
- Apply Matplotlib for customized charts.
- Learn to highlight key trends for analysis reports.
- Combine multiple data metrics visually for better understanding.
- Practice creating publication-ready visualizations.
- Hands-on project allows inclusion of real COVID-19 analysis.
- Demonstrates practical skills in data cleaning, merging, and visualization.
- Provides a completed notebook ready for portfolio display.
- Shows ability to interpret and present complex datasets.
- Enhances credibility for Data Analyst or Health Data Analyst applications.
- Total duration is approximately 100 minutes (~1 hour 40 minutes).
- Fully browser-based environment requires no setup.
- Self-paced learning allows flexibility to pause and resume.
- Focused project ensures hands-on experience in a short time.
- Ideal for learners seeking quick, practical upskilling.
