Data Science: Computational Thinking with Python

Data Science: Computational Thinking with Python

Course
en
English
20 h
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  • From www.edx.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 5 Sequences
  • Introductive Level

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Course details

Syllabus

  • Basics of the Python programming language, and how to use it as a tool for data analysis
  • Tools widely used by industry and academic data scientists, such as Jupyter Notebooks
  • How to use computation to help your data tell a story
  • Fundamental principles and methods of visualization

Prerequisite

None.

Instructors

Ani Adhikari
Teaching Professor of Statistics
UC Berkeley

John DeNero
Giancarlo Teaching Fellow in the EECS Department
UC Berkeley

David Wagner
Professor of Computer Science
UC Berkeley

Editor

The University of California, Berkeley was chartered in 1868, and its flagship campus — envisioned as a "City of Learning" — was established at Berkeley, on San Francisco Bay. Berkeley faculty consists of 1,582 full-time and 500 part-time faculty members dispersed among more than 130 academic departments and more than 80 interdisciplinary research units. Berkeley alumni have received 28 Nobel prizes, and there are eight Nobel Laureates, 32 MacArthur Fellows, and four Pulitzer Prize winners among the current faculty.

In September 2012, to mark Berkeley's commitment to innovation in teaching and learning, The Berkeley Resource Center for Online Education (BRCOE) was formed. The Center is a resource hub and an operational catalyst for all internal campus-wide and external resources to advise, coordinate, and facilitate the University’s online education initiatives, ranging from credit and non-credit courses, to online degree programs and MOOC projects, including the MOOCLab initiative.

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