Chevron Left
Вернуться к Data-driven Astronomy

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

Оценки: 1,225

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


10 сент. 2020 г.

Really amazing course! Gave me insights into how data analysis works in the field of astronomy and how one can use different machine learning techniques to classify the huge amounts of data generated.


28 февр. 2020 г.

Its been amazing to learn about the celestial objects, stars, galaxies. The lectures and quizzes spurred in me to explore new material online. Great hands on exercises in python and machine learning

Фильтр по:

251–275 из 353 отзывов о курсе Data-driven Astronomy

автор: Barbara R

1 мар. 2021 г.

автор: Tatiana S

10 сент. 2019 г.

автор: ZIHAN Z

23 авг. 2018 г.

автор: Clovis G

21 июня 2021 г.

автор: Biswaraj P

18 мая 2021 г.

автор: Ross N

23 авг. 2018 г.

автор: Muhammad B K

5 нояб. 2019 г.

автор: Krishna D

10 дек. 2021 г.

автор: Ujwal K

18 июня 2020 г.

автор: Khalid M

25 июля 2020 г.

автор: Blaye N

22 июля 2019 г.

автор: RK

2 нояб. 2019 г.

автор: Pepe G

4 нояб. 2020 г.

автор: Anurag A

14 сент. 2017 г.

автор: Chien N

22 июня 2021 г.

автор: Stephen G

24 сент. 2017 г.

автор: Hugh K

14 окт. 2022 г.

автор: Harshita M

23 июля 2020 г.

автор: Kendrick A M

27 февр. 2018 г.

автор: Дмитрий З

7 февр. 2022 г.

автор: Francisco J G R

25 июля 2021 г.

автор: In A

15 дек. 2019 г.

автор: Serhii M

19 мар. 2020 г.

автор: Надежда

13 авг. 2017 г.

автор: William M

17 сент. 2021 г.