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Data analysis increasingly involves mining data from
the Internet and handling big datasets. However, students often lack the
knowledge and experience required to take full advantage of the Internet and
social media's data opportunities. This course guides the students to move
their first steps into data mining. The course offers case studies and
exercises in a friendly class environment. Students will learn (by doing) how
to collect and handle web data in their future work. The course covers the
primary skills required to access web data confidently.
The
course is structured in three blocks:
1. an
introductory block covers the essential knowledge for working with big data
(notions of R programming, developing reproducible code, reporting in
automated notebooks, version control, and Git/GitHub; secondary datasets for
social science research & MySQL).
2. A
data access block focuses on web scraping and related tools (introduction to
regular expressions, HTML language, XML, and JSON data structures).
A
third block introduces more advanced data access concepts, such as API
interaction, and allows students to practice with live coding sessions in
class.
Check out the
syllabus and the OLAT page of the course for more detail at this link: https://lms.uzh.ch/auth/RepositoryEntry/17312448525/CourseNode/78100224418873.
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