Data Mining: Theories and Algorithms for Tackling Big Data | 数据挖掘:理论与算法

Обучение бесплатное
Сертификация платная
10 месяцев
О курсе


Despite the large volume of data mining papers and tutorials available on the web, aspiring data scientists find it surprisingly difficult to locate an overview that blends clarity, technical depth and breadth with enough amusement to make big data analytics engaging. This course does just that.

Each module starts with an interesting real-world example that gives rise to the specific research question of interest.

Students are then presented with a general idea of how to tackle this problem along with some intuitive and straightforward approaches.

Finally, a number of representative algorithms are introduced along with concrete examples that show how they function in practice.

While theoretical analysis sometimes overcomplicates things for students, here it’s applied to help them better understand the key features of the techniques.

数据挖掘:理论与算法 | Data Mining: Theories and Algorithms for Tackling Big Data
Unraveling the mysteries of Data Mining and Big Data, this course is a must-have for any budding Data Scientist. 最有趣的理论+最有用的算法=不得不学的数据科学。
Что Вы изучите?
  • Basic data science concepts
  • Typical data mining techniques
  • Applications for data mining
  • A taste of research in data mining
  • Funny stories about data science
Bo Yuan
Bo Yuan
Associate Professor Tsinghua University
Bo is an Associate Professor at Graduate School at Shenzhen, Tsinghua University. He received his Ph.D. in Computer Science from The University of Queensland in 2006.
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.
Data Mining: Theories and Algorithms for Tackling Big Data | 数据挖掘:理论与算法