Getting Digital

Astronomy Data Science With Python Programming

Develop essential physical sciences skills with expert instruction and practical examples.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Master the fundamentals of physical sciences
Apply best practices and industry standards
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry StandardsPython
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of physical sciences
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in physical sciences
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

This course is designed to take you from a beginner to a confident practitioner in Python programming, image processing, and machine learning. Through step-by-step lessons and hands-on projects, you will build a solid foundation in these essential skills and apply them to real-world problems. What You'll Learn:Python Programming: Master Python basics, including data types, variables, loops, conditional statements, and libraries like NumPy and Matplotlib.

Image Processing: Learn how to process digital images using Python, including convolution operations, edge detection, and filters. Machine Learning: Gain a strong understanding of core ML concepts, including Linear and Logistic Regression, with practical coding examples. Deep Learning and CNNs: Build neural networks from scratch, train them using TensorFlow and Keras, and explore convolutional neural networks (CNNs).

Hands-on Projects:You'll work on engaging projects such as:Analyzing real astronomical image datasets like NGC3184 and M87. Building and training machine learning models for classification and regression tasks. Implementing neural networks and CNNs to solve real-world problems using Kaggle datasets.

Who This Course Is For:Beginners with no prior experience in Python or machine learning. Students and professionals looking to strengthen their knowledge of AI and data science. Anyone interested in exploring how programming and AI are applied to real-world scenarios, such as image processing and astronomy.

Provider
Udemy
Estimated Duration
10-20 hours
Language
English
Category
Science & Academia

Topics Covered

Physical SciencesPythonData Science

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
Ready to get started?

View pricing and check out the reviews. See what other learners had to say about the course.

Get started and enroll now
Money-back guarantee might be available
Join thousands of students

This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

Not sure if this is right for you?

Browse More Physical Sciences Courses

Continue Your Learning Journey

Explore more Physical Sciences courses to deepen your skills and advance your expertise.

This comprehensive GCSE Science MCQ Practice Test Course is designed to help students prepare effectively for their exam...
This course has the main purpose to serve as a general introduction to the rigid polyurethane foam (RPUF) industry. RPUF...
Description:General Chemistry is a basic course for a broad range of students from different fields of science and engin...