Big Data Analytics

Обучение бесплатное
Сертификация платная
1 час курса
О курсе

Gain essential skills in today’s digital age to store, process and analyse data to inform business decisions.

In this course, part of the Big Data MicroMasters program, you will develop your knowledge of big data analytics and enhance your programming and mathematical skills. You will learn to use essential analytic tools such as Apache Spark and R.

Topics covered in this course include:

  • cloud-based big data analysis;
  • predictive analytics, including probabilistic and statistical models;
  • application of large-scale data analysis;
  • analysis of problem space and data needs.

By the end of this course, you will be able to approach large-scale data science problems with creativity and initiative.

Big Data Analytics
Learn key technologies and techniques, including R and Apache Spark, to analyse large-scale data sets to uncover valuable business information.
Что Вы изучите?
  • How to develop algorithms for the statistical analysis of big data;
  • Knowledge of big data applications;
  • How to use fundamental principles used in predictive analytics;
  • Evaluate and apply appropriate principles, techniques and theories to large-scale data science problems.
Lewis Mitchell
Lewis Mitchell
Lecturer in Applied Mathematics University of Adelaide
Lewis is a lecturer in applied mathematics at the University of Adelaide. His research focusses on large-scale methods for extracting useful information from online social networks, and on statistical techniques for inference and prediction using these data. He works on building tools for real-time prediction of events like disease outbreaks, elections, and civil unrest.
Simon Tuke
Simon Tuke
Lecturer in Statistics University of Adelaide
Simon is a lecturer in statistics in the School of Mathematical Sciences at the University of Adelaide. His research focuses on statistical modelling of network data in particular methods to access a model’s fit. Simon is also an applied statistician with consulting experience in fields as diverse as predicting when the Maori’s arrived in New Zealand to estimating if cattle walk less after castration.
David Suter
David Suter
Professor of Computer Science University of Adelaide
David is a Professor in the School of Computer Science at The University of Adelaide. Prior to that he was a Professor in the Dept. of Electrical and Computer Systems Engineering at Monash University. His research is vernally in spatial data analysis, image processing and computer vision. A particular focus has been the use of (robust) statistical methods in computer vision. He has taught broadly across computer science and computer systems engineering courses, with a general emphasis on scientific computing.
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.
Big Data Analytics