Курс Python for Data Science

Payment
Обучение бесплатное
Certificate
Сертификация платная
Duration
3 месяца
О курсе

In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?

This course, part of the Data Science MicroMasters program, will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you'll learn how to use:


  • python
  • jupyter notebooks
  • pandas
  • numpy
  • matplotlib
  • git
  • and many other tools.

You will learn these tools all within the context of solving compelling data science problems.

After completing this course, you'll be able to find answers within large datasets by using python tools to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily sharable reports.

By learning these skills, you'll also become a member of a world-wide community which seeks to build data science tools, explore public datasets, and discuss evidence-based findings. Last but not least, this course will provide you with the foundation you need to succeed in later courses in the Data Science MicroMasters program.

Программа
Python for Data Science
Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
Python for Data Science
Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
Python for Data Science
Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
Что Вы изучите?
  • Basic process of data science
  • Python and Jupyter notebooks
  • An applied understanding of how to manipulate and analyze uncurated datasets
  • Basic statistical analysis and machine learning methods
  • How to effectively visualize results
Лекторы
Ilkay Altintas
Ilkay Altintas
Chief Data Science Officer at the San Diego Supercomputer Center UC San Diego
Ilkay Altintas is the chief data science officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the founder and director for the Workflows for Data Science Center of Excellence. She received her Ph.D. degree from the University of Amsterdam in the Netherlands with an emphasis on provenance of workflow-driven collaborative science and she is currently an assistant research scientist at UCSD.
Leo Porter
Leo Porter
Assistant Teaching Professor, Computer Science and Engineering UC San Diego
Leo Porter is an Assistant Teaching Professor at the Department of Computer Science and Engineering at the University of California, San Diego. He received his Ph.D. in Computer Science, specifically computer architecture, from UC San Diego in 2011.
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.