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Master of Engineering in Engineering Management

Want credit towards this degree before you enroll? Join us on February 7th to learn more! Register here!

University of Colorado Boulder logo

Master of Engineering in Engineering Management

University of Colorado Boulder

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Fully accredited online program

Earn the same diploma as students on campus

$20,010 USD total tuition

Flexible pay-as-you-go payment options with no hidden costs or fees

Performance-based admissions

Just start learning and show us you’re ready, regardless of your academic background

Finish in as little as 12 months

Complete 30 courses (30 credit hours) full or part time at your own speed within 8 years

100% online learning

Lecture videos, hands-on projects, and connection with course facilitators and peers

Academics

Through the program, you’ll equip yourself with the necessary skills and knowledge to thrive in the current dynamic business landscape.

As a technical professional or an aspiring manager in the ME-EM program on Coursera, you’ll learn to lead in technology-driven industries through core curriculum on leadership, finance, project management, communication, and electives.

Flexibility
Start on a pathway course and begin working towards your degree on a timeline that’s right for you.
Program length
Choose from six enrollment terms throughout the year. Many students finish in around 12-24 months.
Language
Taught in English with subtitles in English, Arabic, German, Spanish, French, Indonesian, Portuguese-BR, and Thai.
Learn on mobile
Take your studies on the go with mobile-friendly learning on iOS and Android. Some assignments may not be compatible with a mobile device.

Try a degree course today

Sample the Master of Engineering in Engineering Management learning experience and test your skills by enrolling in a non-credit course first. You can always upgrade later to the for-credit experience and pay tuition to apply credit toward the full degree.

Here are some courses you can start with:

Important Dates

Enrollment Open: January 2 - February 21, 2025.

For-credit Course Access: January 13 - March 7, 2025.

Upcoming Events

February 7th - Become a leader in sustainability and the circular economy with CU Boulder Engineering Management Program. Register here!

Important Dates

Enrollment Open: January 2 - February 21, 2025.

For-credit Course Access: January 13 - March 7, 2025.

Upcoming Events

February 7th - Become a leader in sustainability and the circular economy with CU Boulder Engineering Management Program. Register here!

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Build the skills you’ll need in programming, statistics and data analysis

Build a solid foundation for computer science expertise, with key programming concepts and problem-solving techniques using Python, one of the most widely used and versatile programming languages.

A focus on real-life problems and practical exercises will provide you with a strong working knowledge and sought-after computer science skills.

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Curriculum

You’ll build computing-specific academic skills across two distinct areas:

  • Qualitative reasoning skills: Exploring computer ethics, you’ll learn to think critically and communicate effectively about legal, moral and ethical issues related to your field of study.

  • Quantitative reasoning skills: You’ll use data analysis and produce engaging dashboards, apply common descriptive statistics to summarise datasets, and use data visualisation approaches to demonstrate patterns.

  • This module will provide practical experience in applying theoretical programming concepts in creative ways to solve real-world problems. Using Python, one of the most popular and versatile programming languages, you’ll build essential skills in this vital discipline.
  • On completion of this module, you’ll be proficient in implementing and manipulating data structures, managing and analysing data.
  • Topics covered include control flow statements, data structures, object-oriented programming, data wrangling with Pandas, databases and NumPy library.

  • This module provides a comprehensive knowledge base in the mathematics that underpin computer science.
  • You’ll refresh and secure your understanding of arithmetic and algebra, gain an overview of the functions and fundamentals of calculus and trigonometry, and explore a range of other mathematical concepts that will be relevant to your ongoing studies of computer science.
  • Topics covered include quadratic equations and parabolae, number bases and modular arithmetic, sequences and series, and vectors and geometry.

  • You’ll build a strong foundation of statistical knowledge on this module. You’ll grasp the fundamental principles of probability theory, allowing you to understand and apply standard statistical operators and recall essential probability distributions.
  • You’ll perform statistical inference in order to make informed decisions based on data analysis, and construct causal models to meet the requirements of different statistical analysis contexts.
  • Topics covered include discrete and continuous probability distributions, interval estimation, hypothesis testing principles, contingency tables and the chi-squared test, and simple linear regression.

Enrollment for Spring 1 session opens on January 2, 2025

Spring 1 enrollment closes on February 21, 2025.