Astronomy Research Data Analysis With Python

Starting from Python, learn data analysis, data visualizations and image process (beginner to advanced) techniques.

What you'll learn

Python Programming Basics upto Conditionals and Loops

Data Visualization for Tabular Data

Astronomy Image processing and visualization

Hands-on learning approach with practical examples and real-world datasets.

Requirements

No Programming Knowledge or Experience Required

No Astronomy Experience or Knowledge Required

Description

Course Description:Embark on an enlightening journey through the cosmos with our comprehensive Udemy course, "Astronomy Research Data Analysis with Python." This course is designed for astronomy enthusiasts, students, and researchers keen on mastering Python for analyzing astronomical data. With a focus on practical skills and real-world applications, this course simplifies complex concepts, making it accessible to learners with basic programming knowledge.What You'll Learn:Module 1: Starting with Python Dive into Python programming, beginning with the basics. Understand Google Colab, variables, data types, and control flow. Learn about f-strings, user inputs, and functions. This foundation is crucial for handling astronomical data efficiently.Module 2: Tabular Data Visualization Explore the world of tabular data with Pandas, Matplotlib, and Seaborn. Learn how to import libraries, analyze star color data, detect outliers, and create line plots and HR diagrams. You'll gain the ability to visualize and understand complex astronomical datasets.Module 3: Image Data Visualization Uncover the secrets of astronomical image data. Learn about FITS files, and use Python to visualize galaxies like M31. Understand image processing techniques like MinMax and ZScaleInterval scaling, enhancing your ability to interpret celestial images.Module 4: Image Processing | Apply Filters and Extracting Features Delve deeper into image processing. Learn about convolution operations, Gaussian kernels, and feature enhancement. Discover techniques for identifying and extracting features from astronomical images, a skill vital for research and analysis.Feedback, Conclusion, Further Steps Wrap up your learning experience with feedback sessions, a course conclusion, and guidance for future learning paths in astronomy and data analysis.Who This Course is For:Astronomy students and hobbyists looking to apply Python in their studies or projects.Researchers and professionals in astronomy or related fields seeking to enhance their data analysis skills.Programmers interested in expanding their skills into the realm of astronomy and scientific data analysis.Course Features:Hands-on learning approach with practical examples and real-world datasets.Step-by-step guidance, ensuring a solid grasp of each concept.Access to a community of like-minded learners and professionals.Lifetime access to course materials, including updates.Enroll Now:Join us on this exciting journey to unravel the mysteries of the universe with Python. Enroll in "Astronomy Research Data Analysis with Python" today and take the first step towards mastering the art of astronomical data analysis!

Overview

Section 1: Starting with Python

Lecture 1 Introduction to the Program

Lecture 2 Google Colab Introduction

Lecture 3 Comments in Python

Lecture 4 Variables and Constants

Lecture 5 Basic Data Types

Lecture 6 f-Strings

Lecture 7 User Inputs

Lecture 8 Data Type Conversion

Lecture 9 Control Flow

Lecture 10 Functions in Python

Section 2: Tabular Data Visualization using Pandas, Matplotlib and Seaborn

Lecture 11 Introduction about the module 2

Lecture 12 Introduction to the Tabular Data

Lecture 13 Importing the Libraries

Lecture 14 Peeking into the Tabular Data

Lecture 15 Creation of Directory to save Visuals

Lecture 16 First Visualization from Tabular Data

Lecture 17 Customizing and Saving the Visualizations

Lecture 18 Visualizing Star Color Data

Lecture 19 Visualizing the Outliers in the Data

Lecture 20 Line Plots to Visualize the trend in Data

Lecture 21 Creating a Pairplot

Lecture 22 Create HR Diagram

Lecture 23 Downloading the Visualizations

Section 3: Image Data Visualization

Lecture 24 Introducing the Module

Lecture 25 What is an Image?

Lecture 26 Understanding FITS file

Lecture 27 Installing and Importing Libraries

Lecture 28 SkyView Form

Lecture 29 Fetch and Visualize M31 Galaxy in Python the image data

Lecture 30 Fetch and visualize another Image of M31

Lecture 31 Create your own FITS file

Lecture 32 Visualize Distribution of Pixels of M31

Lecture 33 Apply MinMax Pixel Scaling on Pixels of M31

Lecture 34 Different Types of Pixel Scaling

Lecture 35 ZScaleInterval from Astropy

Section 4: Image Processing | Apply Filters and Extracting Features

Lecture 36 Introducing the Module

Lecture 37 Understanding Convolution operation

Lecture 38 Gaussian Kernel for Denoising

Lecture 39 Enhancing the Features in the Image

Lecture 40 Corner Foerstner

Lecture 41 Multiscale Basic (Local) Features

Section 5: Course Conclusion

Lecture 42 Feedback, Conclusion, Further Steps

Astronomy students and hobbyists looking to apply Python in their studies or projects.,Researchers and professionals in astronomy or related fields seeking to enhance their data analysis skills.,Programmers interested in expanding their skills into the realm of astronomy and scientific data analysis.