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Data Modeling and Prediction with R

Learn how to move from exploring data to modeling it with confidence. In this course, you’ll build and interpret linear and logistic regression models in R to uncover relationships, make predictions, and quantify uncertainty. You’ll begin by learning how to fit and interpret simple and multiple linear regression models, then advance to modeling categorical outcomes with logistic regression. Finally, you’ll explore bootstrapping and hypothesis testing to understand and communicate the uncertainty in your results. By the end of this course, you’ll be able to use statistical modeling to make and explain data-driven decisions – an essential skill for data scientists, analysts, and anyone working with real-world data.
Duration 6 Months
Institution Duke University
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into Duke University.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $333
Total Est. Investment $333

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Data Modeling and Prediction with R program at Duke University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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