IBM
Data Science with R - Capstone Project
IBM

Data Science with R - Capstone Project

This course is part of multiple programs.

Jeff Grossman
Yan Luo

Instructors: Jeff Grossman

Sponsored by University of Texas at Austin

13,800 already enrolled

Gain insight into a topic and learn the fundamentals.
4.5

(81 reviews)

Intermediate level
Some related experience required
24 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.5

(81 reviews)

Intermediate level
Some related experience required
24 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame.

  • Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.

  • Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics.

  • Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.

Details to know

Shareable certificate

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Assessments

5 assignments

Taught in English

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When you enroll in this course, you'll also be asked to select a specific program.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 6 modules in this course

What's included

2 videos1 assignment3 app items5 plugins

What's included

1 video1 assignment2 app items3 plugins

At this stage of the Capstone Project, you have gained some valuable working knowledge of data collection and data wrangling. You have also learned a lot about SQL querying and visualization. Congratulations! Now it's time to apply some of your new knowledge and learn about Exploratory Data Analysis (EDA) techniques, again through practice. You can use the datasets you wrangled in the previous Module. However, if you had any issues completing the wrangling, no worries - we have prepared some clean datasets for you to use. You will be asked to complete three labs:

What's included

1 video1 assignment3 app items3 plugins

What's included

1 video1 assignment2 app items2 plugins

What's included

1 video1 assignment1 ungraded lab3 plugins

What's included

2 videos3 readings1 peer review5 plugins

Instructors

Instructor ratings
4.5 (24 ratings)
Jeff Grossman
IBM
2 Courses62,302 learners
Yan Luo
IBM
7 Courses316,467 learners

Offered by

IBM

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4.5

81 reviews

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MP
4

Reviewed on Jun 12, 2024

BT
5

Reviewed on Oct 21, 2023

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