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Build and deploy a stroke prediction model using R
In this project, you’ll help a leading healthcare organization build a model to predict the likelihood of a patient suffering a stroke. The model could help improve a patient’s outcomes. Working with a real-world dataset, you’ll use R to load, clean, process, and analyze the data and then train multiple classification models to determine the best one for making accurate predictions.
Upon completion, you’ll produce a well-validated prediction model that showcases your ability to perform a complete data analysis project involving feature engineering, handling missing data, model evaluation, model selection, and model deployment.
There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.
ROLE: Data Analyst
SKILLS: R, Data Analysis, Predictive Modeling
PREREQUISITES:
Load, clean, explore, manipulate, and visualize data in R,
Use R to build a prediction model
Use R documentations and vignettes to write new codes
Duration
4 Months
Institution
Coursera
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$375
Total Est. Investment
$375
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Build and deploy a stroke prediction model using R program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.