Programming for Data Science

Payment
Обучение бесплатное
Certificate
Сертификация платная
Duration
2 часа курса
О курсе

There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area.

Using practical activities and our innovative ProcessingJS Workspace application you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

You will learn algorithm design as well as fundamental programming concepts such as data selection, iteration and functional decomposition, data abstraction and organisation. In addition to this you will learn how to perform simple data visualisations using ProcessingJS and embed your learning using problem-based assignments.

This course will test your knowledge and skills in solving small-scale data science problems working with real-world datasets and develop your understanding of big data in the world around you.

Программа
Programming for Data Science
Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems.
Programming for Data Science
Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems.
Что Вы изучите?
  • How to analyse data and perform simple data visualisations using ProcessingJS
  • Understand and apply introductory programming concepts such as sequencing, iteration and selection
  • Equip you to study computer science or other programming languages
Лекторы
Katrina Falkner
Katrina Falkner
Head - School of Computer Science University of Adelaide
Katrina has a strong interest in Computer Science Education Research (CSER), mainly in the areas of collaborative and active pedagogy. She has a particular interest in the use of technology to support online learning, including massive open online courses, online collaboration environments and technology-assisted education.
​Claudia Szabo
​Claudia Szabo
Senior Lecturer, School of Computer Science University of Adelaide
Claudia’s main research interests lie in the area of computer systems and computer science education. Her computer science education focus lies in the area of curriculum design and analysis using emerging pedagogical and cognitive theories. In computer systems, she is interested in understanding the effects that interactions between system components have on the behaviour of the system as a whole.
Nick Falkner
Nick Falkner
Associate Professor, School of Computer Science University of Adelaide
Nick loves teaching and does most of his education research into the areas of motivation, time management and effective teaching delivery. He also looks at the role of social networks in forming strong communities for learning, to identify positive and supportive behaviour that will lead to better outcomes for everyone.
Платформа
EdX
Эта платформа предоставляет все курсы бесплатно. Авторами выступают топовые университеты и корпорации, которые стараются удерживать стандарты качества. За несоблюдение дедлайнов, невыполнение домашнего задания студенты теряют баллы. Как и в других платформах, лекционные видео чередуются с практическими заданиями. Обучение проводится на английском, китайском, испанском, французском и хинди.
Programming for Data Science