Data Science with R - Capstone Project
Master data science skills through a comprehensive bike-sharing demand analysis project using R programming.
Master data science skills through a comprehensive bike-sharing demand analysis project using R programming.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM Data Analytics with Excel and R Professional Certificate or Applied Data Science with R Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
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What you'll learn
Collect and process data through web scraping and API integration
Perform data wrangling using R Tidyverse and regular expressions
Conduct exploratory analysis with SQL and visualization tools
Develop predictive models using linear regression
Create interactive dashboards with R Shiny and Leaflet
Present data-driven insights through professional reports
Skills you'll gain
This course includes:
0.25 Hours PreRecorded video
4 quizzes, 1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 6 modules in this course
This capstone project provides hands-on experience in real-world data science applications using R. Students work on a bike-sharing demand analysis project, covering the entire data science workflow from data collection to presentation. The curriculum includes web scraping, data wrangling with Tidyverse, exploratory analysis using SQL and ggplot2, predictive modeling with linear regression, and creating interactive dashboards with Shiny and Leaflet. Through guided labs and practical assignments, learners develop a comprehensive data analysis solution.
Capstone Overview and Data Collection
Module 1 · 4 Hours to complete
Data Wrangling
Module 2 · 4 Hours to complete
Performing Exploratory Data Analysis with SQL, Tidyverse & ggplot2
Module 3 · 3 Hours to complete
Predictive Analysis
Module 4 · 4 Hours to complete
Building a R Shiny Dashboard App
Module 5 · 4 Hours to complete
Present Your Data-Driven Insights
Module 6 · 2 Hours to complete
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.
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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4.6 course rating
76 ratings
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