Chevron Left
Вернуться к Data-driven Astronomy

Отзывы учащихся о курсе Data-driven Astronomy от партнера Сиднейский университет

4.8
Оценки: 431
Рецензии: 126

О курсе

Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits. To analyse this data scientists need to be able to think computationally to solve problems. In this course you will investigate the challenges of working with large datasets: how to implement algorithms that work; how to use databases to manage your data; and how to learn from your data with machine learning tools. The focus is on practical skills - all the activities will be done in Python 3, a modern programming language used throughout astronomy. Regardless of whether you’re already a scientist, studying to become one, or just interested in how modern astronomy works ‘under the bonnet’, this course will help you explore astronomy: from planets, to pulsars to black holes. Course outline: Week 1: Thinking about data - Principles of computational thinking - Discovering pulsars in radio images Week 2: Big data makes things slow - How to work out the time complexity of algorithms - Exploring the black holes at the centres of massive galaxies Week 3: Querying data using SQL - How to use databases to analyse your data - Investigating exoplanets in other solar systems Week 4: Managing your data - How to set up databases to manage your data - Exploring the lifecycle of stars in our Galaxy Week 5: Learning from data: regression - Using machine learning tools to investigate your data - Calculating the redshifts of distant galaxies Week 6: Learning from data: classification - Using machine learning tools to classify your data - Investigating different types of galaxies Each week will also have an interview with a data-driven astronomy expert. Note that some knowledge of Python is assumed, including variables, control structures, data structures, functions, and working with files....

Лучшие рецензии

GM

Jun 30, 2017

Great course with a good balance of code and the rewards to be had from understanding how the code works - proved to be an excellent introduction to Astronomy and confidence builder in Python.

BF

Aug 11, 2019

Such a wonderful course. It had a very good mix of astronomy and computer science. The programming activities were especially good and the lectures were very informative. I highly recommend.

Фильтр по:

1–25 из 125 отзывов о курсе Data-driven Astronomy

автор: Ayush N

Oct 21, 2018

I finished this course today. If you want to learn advanced concepts like machine learning, decision tree classification, SQL, and more; then this is the course for you! I'm a senior in high school, and I'm going to major in Astrophysics. If you love Computer Science this will be an interesting course, as it will show the applications of CS to Astronomy.

автор: Maciej K

Dec 11, 2018

Starting from the basics and going into ml - nice content :) iIloved the idea to solve more interresting problems, not only house-price-predict. I would like to see more of such courses in the future. Thank you :)

автор: Diego J M G

Jan 14, 2019

Muy recomendable

автор: Samrat M

Jan 16, 2019

The course was just epic. Anyone who wants to learn about the application of Machine Learning in the field of Astronomy , this course is a must. The activities will be like the instructor is sitting just by your side, and guiding you, which is what any beginner wants to start their journey. The course is just awesome.

автор: Josh C

Jan 03, 2019

This class is incredible and inspirational. I learned so many highly applicable skills and I am very glad to have taken this class in its entirety. Thank you!

автор: Richard E

Jan 04, 2019

I enjoyed this fusion of programming with Astronomy topics. Note that the exercises use the Python programming language (no substitutes permitted), fairly generic Structured Query Language (SQL) for databases, numpy (science math tools) Python library, scikit-learn (machine learning) Python library, and matplotlib (math & plotting) Python library.

I highly recommend this course, even if you are already experienced in a subset of the above.

Would be interesting: a 2nd more advanced course.

автор: Abdul A

Jan 22, 2019

Excellent presentation and delivery method by the instructors and very good course content. Highly recommend it anyone curious about Universe and to understand it better!

автор: Juan M H

Jan 25, 2019

Besides being a Senior Developer, and Junior Data Scientist, I also am a Self Taught astronomer, and this course has given me a lot of knowledge and insights about astronomy, andways in which I can practice my self learning carrear in astronomy (and maybe astrophysics?) Awesome course! Highly recommended!

автор: Daniel N

Mar 20, 2019

very good course, with clear technical explination and interesting

автор: Atul N

Feb 09, 2019

What I liked about the course was the graded programming assignments, which help to introduce a person to machine learning techniques and other problems in astronomy data processing. Being a physics student by formal education and a star gazer too, I am familiar with the theory but was always curious about how to they measure distances, how do they measure red-shifts etc when the distant galaxies are themselves so faint. This course helped me understand these stuff....

автор: Behzad B A

Jan 27, 2019

Very professional, very productive

автор: Sara D

Apr 08, 2019

Fantastic! I learned a lot. The exercises were really interesting!

автор: Richard O

Apr 01, 2019

Perfect to brush up my Python skills while studying a fascinating subject!

автор: Michael W

Mar 08, 2019

This is a very well organized, interesting, and, quite frankly, fun class. I especially liked being able to do hands-on exercises in Python.

автор: miguel a

Mar 09, 2019

Fue un excelente curso , me ayuda mucho para poder intentar el procesado de unos catalogos de galaxias en especial la parte del machine learning aplicado

автор: Mark M

Mar 18, 2019

Interesting, engaging and informative!

автор: SOURABH S

Dec 23, 2018

Ultimate Course,A proper mixture of Data Science,Statistics,Machine learning and Astronomy.Loved it

автор: Alan M

Oct 12, 2017

Although, I gave a five star, but I have following notes:

It was brilliantly structured on shaping and combining scientific problems with data science to tackle those issue. However, it could use few more examples to add to our current skills. Thank you again. That was the course I was looking for, after taking a course on Machine Learning by Andrea NG, from Stanford University.

автор: Nazarov A P

Jul 17, 2017

Very good intraductional course to modern astronomy that is nowadys more and more science about data. Not so much astronomy theory but good programing tasks, sometimes challenging, especially in the starting weeks. As addition some introduction in machine learning is provided. I would recommend it to everyone interested in data analysis in modern science.

автор: Maksym M

Jun 28, 2017

The course is fantastic for those who want to work in the field of high-energy astrophysics. Many useful skills are taught during the course and many interesting activities are proposed. I highly recommend it.

автор: Anurag A

Sep 14, 2017

Unique course, very much excited to learn new things

автор: Akash M P

Sep 10, 2017

Most of all courses in astronomy and astrophysics are just introduction to subject or provides little advanced theoretical perspective but this is one of the courses which teach us practical astronomy and let us have insights of how astronomers really use physics as well as computers to to get something good out of it.

автор: Cooper P

Sep 28, 2017

I have a profound admiration for this course and its professors.

автор: David B

Nov 02, 2017

Very enjoyable and at times challenging.

автор: Russell O

Jun 20, 2017

Thank you for a very interesting, educational, and ofttimes challenging course. I suspect the instructors and mentors have introduced me to only the tip of the iceberg - 98% of data-driven astronomy lies below the surface and inside enormous datasets/databases. It almost makes me wish life had taken a different course and brought me to this fascinating subject. I would look forward to any further courses from you.