R Data Science Capstone Project
This course is part of multiple programs. Learn more.
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
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Applied Data Science with R, Data Analytics and Visualization with Excel and R
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.
Expert in Data Science and Engineering
Jeff Grossman is a seasoned Data Science and Engineering Subject Matter Expert at IBM, with a robust background that spans pure mathematics, geophysical signal and image processing, medical imaging, and data science. As the founder of 617 Data Solutions Inc., he focuses on guiding organizations through their data science journeys, helping them leverage data for informed decision-making. His company collaborates strategically with the Data and Analytics Team at Missing Link Technologies, ensuring that clients build a solid data foundation from the outset. This groundwork enables actionable intelligence to thrive through customized solutions in data extraction, integration, visualization, automation, machine learning, and artificial intelligence. Passionate about community engagement, Jeff serves as a Subject Matter Expert at Skill-Up Technologies, where he develops educational content for IBM/Coursera courses. He also volunteers with CAMDEA Digital Forum in Alberta, Canada, further demonstrating his commitment to advancing knowledge in the field of data science.
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Frequently asked questions
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