Cosmic Insights: Data-Driven Astronomy and AI Mastery

Course Details

Cosmic Insights: Data-Driven Astronomy and AI Mastery

Data Science

Created by

Vishnu Vasudev

Last Update

September 26, 2023

Created On

September 21, 2023

Description

Astronomy is the captivating science of exploring the universe. It examines stars, planets, galaxies, and more through advanced telescopes and technology. Astronomers uncover the universe's origins, evolution, and fundamental laws, from stellar lifecycles to the mysteries of dark matter and dark energy. This field also encompasses planetary science, the quest for extraterrestrial life, and exciting discoveries like exoplanets and gravitational waves. Above all, astronomy ignites wonder and curiosity about our place in the cosmos.

Overview

Embark on an extraordinary journey with 'Cosmic Insights,' where we merge astronomy and artificial intelligence into a transformative learning experience. Dive into the universe's mysteries, starting with image processing and a broad astronomy introduction. **Master Python for data manipulation and explore the depths of image processing techniques**. Engage in practical observational experiences across various astral domains, while honing advanced programming skills. **Harness the potential of machine learning and deep learning to classify star types. Your journey culminates with 'Galaxy Zoo,' your end-to-end project**. **By course end, you'll emerge as a skilled data scientist, ready to unravel the cosmos through data-driven exploration**.

Features

• Real astronomical data sets for analysis and projects.

• Instructor Led Live Classes

• Lifelong Dashboard access

• Doubt clearing live classes

• Assignment in all the modules

• Quiz in all modules

• Internship Portal Access

• Practical hands-on sessions to reinforce theoretical concepts.

• A final project that allows students to apply their knowledge to a real-world problem.

• Guest lectures from experts in the fields of astronomy and artificial intelligence.

• Opportunities for collaboration with research projects.

What you'll learn

• Foundations of Image Processing

• Astronomical Fundamentals

• Python Programming Proficiency

• Numerical Computing with NumPy

• Data Visualization and Image Processing

• Object-Oriented Programming (OOP)

• Advanced Image Processing Techniques

• Fourier Transforms

• Data Preprocessing

• Feature Detection and Extraction

• Astronomical Data Analysis

• Introduction to Machine Learning

• Hands-on Machine Learning

• Star Type Classification

• Introduction to Deep Learning and Convolutional Neural Networks (CNNs)

• Neural Network Implementation

Prerequisites

Curriculum

24 modules

0. About the Course

Duration • 5 hours

1. Introduction to Image Processing (Theory)

Duration • 1 hour

Binary image

grayscale image

RGB image

Computer Vision

Phases of DIP

Astronomical images

Common image file format

2. Introduction to Astronomy at Large (Theory and Hands-on)

Duration • 1 hour

Details from stars

Observational Astronomy

Radio Astronomy

Infrared Astronomy

Optical Astronomy

High Energy Astronomy

Astronomical Data

FITS data

Google collab

3. Basics of python, Data Types (Hands-on)

Duration • 1 hour

Basic Data types

Operators, List

Python Iterables

Dictionary

4. Advanced Python (Functions and Loops) (Hands-on)

Duration • 1 hour

Functions

Conditionals

Loops

5. Numpy (Hands-on)

Duration • 1 hour

Introduction and application of NumPy in scenarios

6. Matplotlib and Image Processing with OpenCv (Hands-on

Duration • 1 hour

Plotting diagram:

line plot

multiple plots in same canvas

introduction to OpenCv, application of OpenCv

7. OOPs in Python (Hands-on)

Duration • 1 hour

Procedure oriented programming

4 pillars of OOPs, Instance of class

special methods

8. Introduction to Image Processing (Hands-on)

Duration • 1 hour

Cv2 in image processing

read image.

Alpha channel

9. Image Convolution & Gaussian Denoising (Hands-on)

Duration • 1 hour

Convolutional operation

Strides, padding

Denoising

Image sharpening

Median filter

10. Block Matching and 3D Filtering (Hands-on)

Duration • 1 hour

BM3D

Edge filters,

Roberts operator

Sobel operator

Ridge filters

11. Fourier Transforms in Image Processing (Hands-on)

Duration • 1 hour

Discrete Fourier transform step by step operations.

12. Pixel Scaling and Normalization (Hands-on)

Duration • 1 hour

Linear scaling

Z scaling

Log Normalisation

13. Feature Detection and Extraction (Hands-on)

Duration • 1 hour

Canny algorithm,

Multi scale basic features,

Histogram of oriented gradients,

Astropy

14. Astronomical data analysis (FITS Intro) (Hands-on)

Duration • 1 hour

FITS reading,

Overview and data analysis,

Path directories

15. Astronomical data analysis on NGC3184 (Hands-on)

Duration • 1 hour

NGC3184 galaxy’s FITS file,

Plotting and analysis,

How to access FITS files from archives

16. Searching for Black Hole (Hands-on)

Duration • 2 hours

Astroquery,

How to make your own FITS file,

Astropy visualization modules,

Black hole

17. Intro to Machine Learning (Theory)

Duration • 1 hour

Supervised,

Unsupervised and reinforced learning,

Optimisation,

Cost function,

18. Intro to Machine Learning (Hands-on)

Duration • 1 hour

Linear regression,

Least square method,

R2 score,

Gradient descent,

19. Star Type detection using Machine Learning - Project (Hands-on)

Duration • 1 hour

HR diagram.

Creating data frame.

Training model.

20. Intro to Deep Learning - Neural Networks (Theory)

Duration • 1 hour

Deep learning,

Artificial neurons,

Neural network,

Activation function,

ReLu

SoftMax

21. Intro to Convolutional NN (Theory)

Duration • 1 hour

Convolutional Neural Network,

Architecture, convolutional operation,

Strides,

Padding,

Pooling, fully connected,

Forward propagation,

ANN learn,

Back propagation

22. Implementation of NN (Hands-on)

Duration • 1 hour

Building neural network from scratch

Preparing data, weight & bias

Defining nodes

Sigmoid activation

Forward & backward propagation

Learning rate, training iteration

Cost function

23. Building Final Project - Galaxy Zoo (Hands-on)

Duration • 2 hours

Data set description

Read csv file.

Training and testing

Visualise random images.

Preprocessing images

Make the model.

Fit the model.

Implement on test data.

Culmination

Instructors

Vishnu Vasudev

Vishnu Vasudev embodies a fascinating journey - an M.Tech. in Electronics and a UGCNET scholar who evolved from a project engineer and dedicated assistant professor to become a Research Fellow in Astrophysics at the prestigious College of Engineering, Chengannur. Beyond academia, he's a celebrated YouTuber, author of two enlightening books on Astrophysics, and a distinguished Abdul Kalam Doctoral Fellow. His multifaceted expertise and passion illuminate both the scientific and educational realms.

Sign in

Sign up

Course Details