Description

• Analyze public datasets to identify tourist trends over time in a location.
• Include insights like peak seasons, visitor demographics, and top attractions.
• Tech Stack: Python, Pandas, NumPy, Seaborn, Scikit-learn, Matplotlib.

What You Will Learn:

✅ Explore and analyze datasets to uncover key tourism trends and insights.
✅ Identify peak tourist seasons based on historical data and patterns.
✅ Analyze visitor demographics to understand traveler preferences and behaviors.
✅ Visualize data using Seaborn & Matplotlib for insightful charts and graphs.
✅ Perform data preprocessing with Pandas and NumPy for efficient analysis.
✅ Apply machine learning models using Scikit-learn to predict tourist trends.

Who Should Take This Course?

🔹 Aspiring data analysts looking to work with real-world tourism data.
🔹 Students and researchers interested in tourism trends and data-driven insights.
🔹 Business professionals seeking to leverage data for strategic tourism planning.
🔹 Python enthusiasts eager to apply NumPy, Pandas, and Seaborn in practical projects.
🔹 Anyone interested in data science and learning practical applications of Python, visualization, and machine learning.