University of Colorado Boulder - Statistical Learning for Data Science Specialization

Offered byCoursera
Public/Government Institute

Statistical Learning for Data Science Specialization
at
Coursera
Overview

Advanced Stats for Data Science Mastery. Master knowledge and skills to communicate model choices and interpretations effectively

Duration	4 months
Total fee	Free
Mode of learning	Online
Official Website	Explore Free Course
Credential	Certificate

Statistical Learning for Data Science Specialization

Table of content

Overview
Highlights
Course Details
Curriculum

Statistical Learning for Data Science Specialization
at
Coursera
Highlights

Earn a Certificate upon completion
Skills -Splines,Unsupervised Learning,regression,R Programming,Resampling,Statistics,Data Science,Selection,Trees,Support Vector Machine (SVM)

Statistical Learning for Data Science Specialization
at
Coursera
Course details

Skills you will learn

Regression Statistics Communication skills Data Science

More about this course

Statistical Learning is a crucial specialization for those pursuing a career in data science or seeking to enhance their expertise in the field. This program builds upon your foundational knowledge of statistics and equips you with advanced techniques for model selection, including regression, classification, trees, SVM, unsupervised learning, splines, and resampling methods. Additionally, you will gain an in-depth understanding of coefficient estimation and interpretation, which will be valuable in explaining and justifying your models to clients and companies. Through this specialization, you will acquire conceptual knowledge and communication skills to effectively convey the rationale behind your model choices and coefficient interpretations.
This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Applied Learning Project
Throughout the specialization, learners will complete many programming assignments designed to help learners master statistical learning concepts, including regression, classification, trees, SVM, unsupervised learning, splines, and resampling methods.