R Data Science Capstone Project
Apply practical data science skills using R through a real-world project. Master data analysis, visualization, and modeling techniques.
Apply practical data science skills using R through a real-world project. Master data analysis, visualization, and modeling techniques.
This comprehensive capstone project allows students to apply their data science skills in a real-world context. Acting as data scientists, participants will work with actual datasets to perform data collection, analysis, and visualization using R. The course emphasizes practical application of Tidyverse for data wrangling, SQL for data exploration, ggplot2 for visualization, and linear regression for modeling. Students will create interactive dashboards and conclude with a professional data analysis presentation including an executive summary for stakeholders.
Instructors:
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What you'll learn
Handle and prepare data for modeling including missing value treatment
Conduct exploratory data analysis using descriptive statistics
Create data visualizations using ggplot2 and interactive dashboards
Perform statistical hypothesis testing and linear regression
Develop professional presentations and executive summaries
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Module Description
This capstone project focuses on applying practical data science skills using R programming. Students work with real-world datasets to perform comprehensive data analysis, including data collection, wrangling, exploration, and visualization. The course emphasizes hands-on experience with tools like Tidyverse and ggplot2, culminating in creating interactive dashboards and presenting findings to stakeholders through executive summaries.
Fee Structure
Instructors
AI and Machine Learning Expert at IBM Canada
Yan Luo serves as a Data Scientist and Developer at IBM Canada, where he applies his expertise in machine learning and artificial intelligence to develop innovative cognitive applications across diverse domains including software repository mining, personalized health management, wireless networks, and digital banking. After earning his Ph.D. in Machine Learning from the University of Western Ontario, he has contributed significantly to technical education through developing and teaching multiple data science courses, including Applied Data Science Capstone, Machine Learning Capstone, and Introduction to R Programming for Data Science. His work focuses on practical applications of AI and cognitive computing, bridging the gap between theoretical machine learning concepts and real-world business solutions.
41 Courses
A Distinguished Data Scientist Advancing Analytics Education and Business Intelligence
Jeff Grossman serves as a Data Science and Engineering Subject Matter Expert at Skill-Up Technologies while leading 617 Data Solutions Inc., a company he founded to guide organizations in their data science journey. With a diverse background spanning Pure Mathematics, Geophysical Signal & Image Processing, Medical Imaging, and Data Science & Engineering, he has established himself as an expert in algorithm development and data-driven decision-making. Through his company's strategic partnership with MLT's Data and Analytics Team, he focuses on building comprehensive data foundations that enable actionable intelligence through customized data extraction, integration, visualization, automation, and artificial intelligence solutions. His commitment to education and community service is demonstrated through his role developing data-related educational content for IBM/Coursera courses and his volunteer work with CAMDEA Digital Forum as an Associate Member in Alberta, Canada. His course portfolio includes "Data Science with R - Capstone Project" and "ETL and Data Pipelines with Shell, Airflow and Kafka," reaching thousands of learners worldwide through the IBM Skills Network platform.
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