Journey into Data Science with Python

Intro to Time Series Analysis with Airline Data

This data-heavy course focuses on trends and patterns in air travel history. Using complex visualizations and time series analysis, you will learn about growth trajectories and seasonal fluctuations in the air travel sector.

Lessons and practices

Exploring the Flights Dataset: First Impressions

Slightly Shifting our Spaceship: Adjusting our View on Flight Data

Navigating Through the Turbulence: Dataset Entry Count Issue

Navigating the Cosmos: Total Entries and Dimensions of the Airline Dataset

Flight Data Exploration: Final Takeoff

Visualizing Trends in Air Travel with Line Plots

Plotting July Passenger Counts Over a Decade

Debugging the Flight Passenger Trends Plot

Creating a Line Plot to Visualize Monthly Passenger Counts

Visualizing Yearly Total Passenger Counts with a Line Plot

Visualizing Seasonal Trends in Air Travel Passenger Counts

Analyzing Monthly Trends in Air Travel Passenger Counts

Debugging Monthly Passenger's Count Plot

Customizing a Line Plot for Monthly Passenger Counts Visualization

Visualizing Seasonal Trends in Air Travel From Scratch

Creating and Visualizing a Heatmap of Air Travel Data

Altering Heatmap's Color Scheme

Debugging Heat Map Creation

Enhancing the Heatmap Visualization of Monthly Airline Passenger Counts

Crafting a Detailed Heatmap from Scratch

Predicting and Visualizing Future Flight Traffic with Linear Regression

Predicting Far Beyond: The Passenger Counts of 1975!

Flight to the Future: Debugging Passenger Prediction

Predicting the Sky Traffic: Next Decade's Passenger Counts

Predicting Decade Passenger Counts using Linear Regression

Drawing the Future: Predicting Passenger Trends with Regression

Interested in this course? Learn and practice with Cosmo!

Practice is how you turn knowledge into actual skills.