Data8.org Website Review

The UC Berkeley Foundations of Data Science course combines three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one an*lyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on an*lysis of real-world datasets, including economic data, docu*ent collections, geographical data, and social networks. It delves into social issues surrounding data an*lysis such as privacy and design. Each offering site includes links to as*ignments, slides, and readings. You are welcome to use any of the materials you find. All materials for the course, including the textbook and as*ignments, are available for free online under a Creative Commons license. textbook that includes interactive Jupyter notebooks and public data sets for all examples. The textbook source is maintained as an open are available as Jupyter notebooks. The notebooks as*ume a Python 3 installation with the standard modules from an Anaconda installation linked from the respective course calendars. To request access to the source of the slides for instructional purposes, please fill out our All of the software components of the course are maintained as open-source projects. We encourage you to contact us if you want any explicitly does not support row indexes, hierarchical indexes, time series data, missing values, slicing, and many other advanced features that can complicate table manipulation for novices. The charting features use Matplotlib, but customize the output to match the simplify working with tables and geojson files. While the datascience module can certainly be used outside the context of the course, it was specifically designed to support the Data 8 curriculum, while setting up students to transition to more standard tools such as Pandas. client-side tests available to students at any time and server-side tests intended for correctness-based grading. As*ignments are