Improve your statistics skills for data science. Learn the statistics required for success in data science.
Suggested by: Coursera (What is Coursera?)
No prior knowledge required
No unnecessary risks
Statistical modeling is at the heart of data science. Well-designed statistical models allow data scientists to draw conclusions about the world from the limited information available in their data. In this three-unit series, learners will add a number of intermediate and advanced statistical modeling techniques to their data science toolbox. In particular, learners will focus on the future and application of:
The emphasis will be on analyzing real data using the R programming language.
This internship can be taken for academic credit as part of the Master of Science in Data Science (MS-DS) program offered by CU Boulder on the Coursera platform. The MS-DS is an interdisciplinary program that brings together faculty from various units at the university, such as:
With admissions based on performance and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and professional experience in computer science, information science, mathematics, and statistics. More information about the MS-DS program can be found here .
Learners will become proficient in the application and application of statistical models through automatically graded and peer-reviewed Jupyter Notebook assignments. In these assignments, learners will use real-world data and advanced modal statistics techniques to answer important scientific and business questions.
