Online dating research at berkley
Offered through: Information Terms offered: Summer 2018, Spring 2018, Fall 2017 Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry.
Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences.
The curriculum includes research design and applications for data and analysis, storing and retrieving data, exploring and analyzing data, identifying patterns in data, and effectively visualizing and communicating data.
MIDS features a project-based approach to learning and encourages the pragmatic application of a variety of different tools and methods to solve complex problems.
Offered twice a year, each four- to five-day immersion will be custom crafted to deliver additional learning, networking, and community-building opportunities.
Offered through: Information Terms offered: Summer 2018, Spring 2018, Fall 2017 This fast-paced course gives students fundamental Python knowledge necessary for advanced work in data science.
Graduates of the program will be able to: The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning.
Know how to use Python to extract data from different type of files and other sources.
Objectives Outcomes Student Learning Outcomes: Be able to design, reason about, and implement algorithms for solving computational problems. Information management, information retrieval, metadata, library services.
Be able to generate an exploratory analysis of a data set using Python.
Be able to navigate a file system, manipulate files, and execute programs using a command line interface. Be fluent in Python syntax and familiar with foundational Python object types.
Be prepared for further programming challenges in more advanced data science courses.