In today’s market, product, process, and service quality is a necessity for a competitive edge in any business. Consumers and customers expect (and demand) high-quality products and services from their suppliers. Knowing how to improve quality affects more than just quality–it affects cost, market share, productivity, employee morale, and company reputation. Learning and applying the systems, strategies, and tools associated with quality improvement can allow a business to stay competitive, reduce cost, increase productivity, and improve both morale and brand loyalty.

In this online data science specialization, you will learn about the concepts, tools, and techniques used in the management and measurement of quality, productivity, and competitiveness in an international business environment. You will learn how to manage, describe, and analyze data using applied statistics; how to assess quality through time for different types of data encountered in business and industry; and how to analyze measurement systems.

By completing this specialization, you will be able to:

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

Courses

  • Managing, Describing & Analyzing Data
  • Stability & Capability in Quality Improvement (Coming Soon)
  • Measurement Systems Analysis (Coming Soon)

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. Learn more about the MS-DS program.

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