Data Science Methods for Quality Improvement, Short Course | Part time online | Coursera | United States
1 months
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Launch your career in data science with this Data Science Methods for Quality Improvement course offered by Coursera in partnership with University of Colorado Boulder. Master strategies in data science methods for quality improvement.

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Data analysis skills are widely sought by employers, both nationally and internationally. This Data Science Methods for Quality Improvement course offered by Coursera in partnership with University of Colorado Boulder is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability.

By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown. Whether you are looking for a job in data analytics, operations, or just want to be able to do more with data, this specialization is a great way to get started in the field. 

Learners are encouraged to complete this specialization in the order the courses are presented.

This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics.

Applied Learning Project

Learners develop an understanding of how to manage, describe, and analyze continuous and discrete data using examples from business and industry. They explore how to assess processes for sources of variation through time as well as determine process capability with respect to customer requirements. Learners gain familiarity with the analysis procedures to assess measurement systems for continuous and discrete data in order to make decisions regarding the capability and acceptability of the measurement system. Assignments require learners to perform analyses for various data types and scenarios, interpret results, and make appropriate decisions.

What You Will Learn:

  • Manage, describe, and analyze data using applied statistics
  • Analyze measurement systems to ensure their stability and capability
  • Apply continuous and/or discrete data methods for process analysis, improvement, and ongoing management in a business or workplace

Skills You Will Gain:

  • Data Science
  • Data Analysis
  • Process Engineering
  • Rstudio
  • Quality Improvement

Programme Structure

Courses include:

  • Managing, Describing, and Analyzing Data
  • Stability and Capability in Quality Improvement
  • Measurement Systems Analysis

Key information


  • Part-time
    • 1 months
    • Flexible

Start dates & application deadlines

You can apply for and start this programme anytime.





Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Intermediate level

  • Recommended experience: Familiarity with RStudio and applied statistics is recommended.

Tuition Fee

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  • International

    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 1 months.
  • National

    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 1 months.

You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access.


Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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