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freeCodeCamp

Python Data Analysis and Visualization Course – Astronomical Data

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Overview

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Embark on a comprehensive 6.5-hour course exploring data analysis, visualization, and image processing techniques using real-world astronomical data. Master Python fundamentals, delve into tabular datasets, create various visualizations using matplotlib and seaborn, and learn advanced image processing methods. Gain hands-on experience with FITS files, pixel scaling, convolution operations, and feature enhancement filters. Perfect for beginners, this course simplifies complex concepts through practical, step-by-step tutorials, culminating in the ability to analyze and visualize astronomical data effectively.

Syllabus

⌨️ Introduction to Course
⌨️ Introduction to Google Colab
⌨️ Python Comments
⌨️ Variables and Constants
⌨️ Basic Data Types
⌨️ f-string
⌨️ User inputs
⌨️ Data Type Conversions
⌨️ Control Flow
⌨️ Functions
⌨️ Intro to Tabular Dataset
⌨️ Importing the libraries for tabular dataset
⌨️ Exploring the tabular dataset
⌨️ Creating First Visualization with barplot matplotlib
⌨️ Adding customization to barplot
⌨️ Creating bargraph using Seaborn
⌨️ Visusalizing outliers using boxplot
⌨️ Introducing subplots using matplotlib
⌨️ Line plots
⌨️ Pair plot and scatter plot
⌨️ Creating HR Diagram
⌨️ Downloading visualizations
⌨️ Understanding Images, pixels, grayscale and colors
⌨️ What are FITS file?
⌨️ Installing Astroquery
⌨️ SkyView Form - Virtual Telescope
⌨️ Visualize Andromeda galaxy
⌨️ Creating FITS file and testing
⌨️ Pixel Distribution
⌨️ MinMax Pixel Scaling
⌨️ Standard Scaling, Log Normalization, Square root normalization
⌨️ ZScaleInterval
⌨️ Convolution Operation - Why? Why? and Demonstration
⌨️ Gaussian Denoising
⌨️ Enhancing features with Meijering and Sato filter
⌨️ Corner Foerstner - What and How to use it in Python
⌨️ Multiscale Basic Features using skimage
⌨️ Conclusion

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Reviews

5.0 rating, based on 2 Class Central reviews

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  • Profile image for Frederick Kwame Molah
    Frederick Kwame Molah
    It is an interesting course to do. The instructor made concepts very easy to grasp. Often softwares like excel and the likes are easy when it comes to visualizations (mostly drag and drop) unlike the programming languages. He took his time to break terminologies down for easy following. I recommend this course to anyone who wants you do visualizations.
  • Profile image for Devarsh Prajapati
    Devarsh Prajapati
    Great course! Clear lessons, hands-on Python projects, and insightful astronomy applications.
    Insightful course bridging astronomy and Python;
    great for learning real data analysis
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